From 3e376c4090b401bdb3487649ff2c56cad2fbc294 Mon Sep 17 00:00:00 2001 From: Torch-TensorRT Github Bot Date: Thu, 12 Dec 2024 17:38:40 +0000 Subject: [PATCH] docs: [Automated] Regenerating documenation for 93b5b8f Signed-off-by: Torch-TensorRT Github Bot --- .../classtorch__tensorrt_1_1DataType.html | 4 +- ...rch__tensorrt_1_1Device_1_1DeviceType.html | 4 +- .../classtorch__tensorrt_1_1TensorFormat.html | 4 +- ...ensorrt_1_1ptq_1_1Int8CacheCalibrator.html | 4 +- ...ch__tensorrt_1_1ptq_1_1Int8Calibrator.html | 4 +- ...8h_1a18d295a837ac71add5578860b55e5502.html | 4 +- ...8h_1a282fd3c0b1c3a215148ae372070e1268.html | 4 +- ...8h_1a31398a6d4d27e28817afb0f0139e909e.html | 4 +- ...8h_1a35703561b26b1a9d2738ad7d58b27827.html | 4 +- ...8h_1abd1465eb38256d3f22cc1426b23d516b.html | 4 +- ...8h_1abe87b341f562fd1cf40b7672e4d759da.html | 4 +- ...8h_1ad19939408f7be171a74a89928b36eb59.html | 4 +- ...8h_1adad592a7b1b7eed529cdf6acd584c883.html | 4 +- docs/_cpp_api/dir_cpp.html | 4 +- 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.../dynamo/refit_engine_example.html | 8 +- .../dynamo/torch_compile_advanced_usage.html | 4 +- .../dynamo/torch_compile_resnet_example.html | 4 +- .../torch_compile_stable_diffusion.html | 4 +- .../torch_compile_transformers_example.html | 4 +- .../dynamo/torch_export_cudagraphs.html | 4 +- .../dynamo/torch_export_gpt2.html | 4 +- .../dynamo/torch_export_llama2.html | 4 +- .../_rendered_examples/dynamo/vgg16_ptq.html | 4 +- .../dynamo/weight_streaming_example.html | 4 +- docs/tutorials/_rendered_examples/index.html | 4 +- .../_rendered_examples/triton/index.html | 4 +- docs/tutorials/notebooks.html | 4 +- .../serving_torch_tensorrt_with_triton.html | 4 +- docs/user_guide/dynamic_shapes.html | 4 +- docs/user_guide/mixed_precision.html | 4 +- docs/user_guide/runtime.html | 4 +- docs/user_guide/saving_models.html | 4 +- docs/user_guide/torch_tensorrt_explained.html | 4 +- docs/user_guide/using_dla.html | 4 +- 162 files changed, 534 insertions(+), 389 deletions(-) diff --git a/docs/_cpp_api/classtorch__tensorrt_1_1DataType.html b/docs/_cpp_api/classtorch__tensorrt_1_1DataType.html index 7f441d0a48..a19afe063c 100644 --- a/docs/_cpp_api/classtorch__tensorrt_1_1DataType.html +++ b/docs/_cpp_api/classtorch__tensorrt_1_1DataType.html @@ -10,7 +10,7 @@ - Class DataType — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Class DataType — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
- v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
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- v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
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- v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
diff --git a/docs/_cpp_api/classtorch__tensorrt_1_1ptq_1_1Int8CacheCalibrator.html b/docs/_cpp_api/classtorch__tensorrt_1_1ptq_1_1Int8CacheCalibrator.html index 3bcf4278e3..3820e581e8 100644 --- a/docs/_cpp_api/classtorch__tensorrt_1_1ptq_1_1Int8CacheCalibrator.html +++ b/docs/_cpp_api/classtorch__tensorrt_1_1ptq_1_1Int8CacheCalibrator.html @@ -10,7 +10,7 @@ - Template Class Int8CacheCalibrator — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Template Class Int8CacheCalibrator — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
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diff --git a/docs/_cpp_api/define_macros_8h_1a18d295a837ac71add5578860b55e5502.html b/docs/_cpp_api/define_macros_8h_1a18d295a837ac71add5578860b55e5502.html index f8ed97222c..f4c55d5f8d 100644 --- a/docs/_cpp_api/define_macros_8h_1a18d295a837ac71add5578860b55e5502.html +++ b/docs/_cpp_api/define_macros_8h_1a18d295a837ac71add5578860b55e5502.html @@ -10,7 +10,7 @@ - Define STR — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Define STR — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
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diff --git a/docs/_cpp_api/define_macros_8h_1adad592a7b1b7eed529cdf6acd584c883.html b/docs/_cpp_api/define_macros_8h_1adad592a7b1b7eed529cdf6acd584c883.html index f511d8b41b..b748b44457 100644 --- a/docs/_cpp_api/define_macros_8h_1adad592a7b1b7eed529cdf6acd584c883.html +++ b/docs/_cpp_api/define_macros_8h_1adad592a7b1b7eed529cdf6acd584c883.html @@ -10,7 +10,7 @@ - Define TORCH_TENSORRT_VERSION — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Define TORCH_TENSORRT_VERSION — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
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diff --git a/docs/_cpp_api/dir_cpp_include.html b/docs/_cpp_api/dir_cpp_include.html index da4c5edbea..b109cba7a1 100644 --- a/docs/_cpp_api/dir_cpp_include.html +++ b/docs/_cpp_api/dir_cpp_include.html @@ -10,7 +10,7 @@ - Directory include — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Directory include — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -273,7 +273,7 @@
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diff --git a/docs/_cpp_api/enum_torch__tensorrt_8h_1a3fbe5d72e4fc624dbd038853079620eb.html b/docs/_cpp_api/enum_torch__tensorrt_8h_1a3fbe5d72e4fc624dbd038853079620eb.html index 318ec372f7..83914792a3 100644 --- a/docs/_cpp_api/enum_torch__tensorrt_8h_1a3fbe5d72e4fc624dbd038853079620eb.html +++ b/docs/_cpp_api/enum_torch__tensorrt_8h_1a3fbe5d72e4fc624dbd038853079620eb.html @@ -10,7 +10,7 @@ - Enum EngineCapability — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Enum EngineCapability — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
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diff --git a/docs/_cpp_api/file_cpp_include_torch_tensorrt_logging.h.html b/docs/_cpp_api/file_cpp_include_torch_tensorrt_logging.h.html index 5a15ec4a4e..6550ee87d5 100644 --- a/docs/_cpp_api/file_cpp_include_torch_tensorrt_logging.h.html +++ b/docs/_cpp_api/file_cpp_include_torch_tensorrt_logging.h.html @@ -10,7 +10,7 @@ - File logging.h — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + File logging.h — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -273,7 +273,7 @@
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diff --git a/docs/_cpp_api/file_cpp_include_torch_tensorrt_ptq.h.html b/docs/_cpp_api/file_cpp_include_torch_tensorrt_ptq.h.html index 9dc114f14f..16e28ef02f 100644 --- a/docs/_cpp_api/file_cpp_include_torch_tensorrt_ptq.h.html +++ b/docs/_cpp_api/file_cpp_include_torch_tensorrt_ptq.h.html @@ -10,7 +10,7 @@ - File ptq.h — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + File ptq.h — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -273,7 +273,7 @@
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diff --git a/docs/_cpp_api/function_logging_8h_1af8f3443813315af7901903d25dd495cc.html b/docs/_cpp_api/function_logging_8h_1af8f3443813315af7901903d25dd495cc.html index 965750fc38..0aa5e2c3f6 100644 --- a/docs/_cpp_api/function_logging_8h_1af8f3443813315af7901903d25dd495cc.html +++ b/docs/_cpp_api/function_logging_8h_1af8f3443813315af7901903d25dd495cc.html @@ -10,7 +10,7 @@ - Function torch_tensorrt::logging::set_logging_prefix — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Function torch_tensorrt::logging::set_logging_prefix — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
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diff --git a/docs/_cpp_api/function_ptq_8h_1a226e3c83379d1012cde8578c1c86b16c.html b/docs/_cpp_api/function_ptq_8h_1a226e3c83379d1012cde8578c1c86b16c.html index 4de3ae6a67..c91d617afa 100644 --- a/docs/_cpp_api/function_ptq_8h_1a226e3c83379d1012cde8578c1c86b16c.html +++ b/docs/_cpp_api/function_ptq_8h_1a226e3c83379d1012cde8578c1c86b16c.html @@ -10,7 +10,7 @@ - Template Function torch_tensorrt::ptq::make_int8_cache_calibrator — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Template Function torch_tensorrt::ptq::make_int8_cache_calibrator — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
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diff --git a/docs/_cpp_api/function_ptq_8h_1a6186e305f47c1d94b6130ef6c7f7e178.html b/docs/_cpp_api/function_ptq_8h_1a6186e305f47c1d94b6130ef6c7f7e178.html index c0f3f3c3dd..4a3e7ca6db 100644 --- a/docs/_cpp_api/function_ptq_8h_1a6186e305f47c1d94b6130ef6c7f7e178.html +++ b/docs/_cpp_api/function_ptq_8h_1a6186e305f47c1d94b6130ef6c7f7e178.html @@ -10,7 +10,7 @@ - Template Function torch_tensorrt::ptq::make_int8_calibrator — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Template Function torch_tensorrt::ptq::make_int8_calibrator — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
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diff --git a/docs/_cpp_api/function_torch__tensorrt_8h_1a5b405fd3bf3c8fc2e2a54cbbab979797.html b/docs/_cpp_api/function_torch__tensorrt_8h_1a5b405fd3bf3c8fc2e2a54cbbab979797.html index 1efda8d593..ffe6dc3ff3 100644 --- a/docs/_cpp_api/function_torch__tensorrt_8h_1a5b405fd3bf3c8fc2e2a54cbbab979797.html +++ b/docs/_cpp_api/function_torch__tensorrt_8h_1a5b405fd3bf3c8fc2e2a54cbbab979797.html @@ -10,7 +10,7 @@ - Function torch_tensorrt::torchscript::check_method_operator_support — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Function torch_tensorrt::torchscript::check_method_operator_support — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
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diff --git a/docs/_cpp_api/function_torch__tensorrt_8h_1a6e19490a08fb1553c9dd347a5ae79db9.html b/docs/_cpp_api/function_torch__tensorrt_8h_1a6e19490a08fb1553c9dd347a5ae79db9.html index 28425dd493..f1e71683e4 100644 --- a/docs/_cpp_api/function_torch__tensorrt_8h_1a6e19490a08fb1553c9dd347a5ae79db9.html +++ b/docs/_cpp_api/function_torch__tensorrt_8h_1a6e19490a08fb1553c9dd347a5ae79db9.html @@ -10,7 +10,7 @@ - Function torch_tensorrt::torchscript::compile — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Function torch_tensorrt::torchscript::compile — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
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diff --git a/docs/_cpp_api/function_torch__tensorrt_8h_1ae8d56472106eeef37fbe51ff7f40c9b2.html b/docs/_cpp_api/function_torch__tensorrt_8h_1ae8d56472106eeef37fbe51ff7f40c9b2.html index 81e3e933aa..8a7eb659e9 100644 --- a/docs/_cpp_api/function_torch__tensorrt_8h_1ae8d56472106eeef37fbe51ff7f40c9b2.html +++ b/docs/_cpp_api/function_torch__tensorrt_8h_1ae8d56472106eeef37fbe51ff7f40c9b2.html @@ -10,7 +10,7 @@ - Function torch_tensorrt::torchscript::convert_method_to_trt_engine — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Function torch_tensorrt::torchscript::convert_method_to_trt_engine — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
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diff --git a/docs/_cpp_api/namespace_torch_tensorrt.html b/docs/_cpp_api/namespace_torch_tensorrt.html index 7f5871ee42..90b2b0d9d4 100644 --- a/docs/_cpp_api/namespace_torch_tensorrt.html +++ b/docs/_cpp_api/namespace_torch_tensorrt.html @@ -10,7 +10,7 @@ - Namespace torch_tensorrt — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Namespace torch_tensorrt — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
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diff --git a/docs/_cpp_api/namespace_torch_tensorrt__logging.html b/docs/_cpp_api/namespace_torch_tensorrt__logging.html index bc31cc44f5..857cf65741 100644 --- a/docs/_cpp_api/namespace_torch_tensorrt__logging.html +++ b/docs/_cpp_api/namespace_torch_tensorrt__logging.html @@ -10,7 +10,7 @@ - Namespace torch_tensorrt::logging — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Namespace torch_tensorrt::logging — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
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diff --git a/docs/_cpp_api/namespace_torch_tensorrt__torchscript.html b/docs/_cpp_api/namespace_torch_tensorrt__torchscript.html index 0143c721fe..44f5fcd0ea 100644 --- a/docs/_cpp_api/namespace_torch_tensorrt__torchscript.html +++ b/docs/_cpp_api/namespace_torch_tensorrt__torchscript.html @@ -10,7 +10,7 @@ - Namespace torch_tensorrt::torchscript — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Namespace torch_tensorrt::torchscript — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
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diff --git a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_logging.h.html b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_logging.h.html index 37150367c7..478d4736dc 100644 --- a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_logging.h.html +++ b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_logging.h.html @@ -10,7 +10,7 @@ - Program Listing for File logging.h — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Program Listing for File logging.h — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -273,7 +273,7 @@
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diff --git a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_macros.h.html b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_macros.h.html index 6310c51d12..339359b571 100644 --- a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_macros.h.html +++ b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_macros.h.html @@ -10,7 +10,7 @@ - Program Listing for File macros.h — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Program Listing for File macros.h — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -273,7 +273,7 @@
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diff --git a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_ptq.h.html b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_ptq.h.html index 1745e2bff8..a919b4d250 100644 --- a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_ptq.h.html +++ b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_ptq.h.html @@ -10,7 +10,7 @@ - Program Listing for File ptq.h — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Program Listing for File ptq.h — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -273,7 +273,7 @@
- v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
diff --git a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_torch_tensorrt.h.html b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_torch_tensorrt.h.html index 9daf0fd135..7c99e4f5d1 100644 --- a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_torch_tensorrt.h.html +++ b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_torch_tensorrt.h.html @@ -10,7 +10,7 @@ - Program Listing for File torch_tensorrt.h — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Program Listing for File torch_tensorrt.h — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -273,7 +273,7 @@
- v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
diff --git a/docs/_cpp_api/structtorch__tensorrt_1_1Device.html b/docs/_cpp_api/structtorch__tensorrt_1_1Device.html index 3ad2ff26c8..51c573d626 100644 --- a/docs/_cpp_api/structtorch__tensorrt_1_1Device.html +++ b/docs/_cpp_api/structtorch__tensorrt_1_1Device.html @@ -10,7 +10,7 @@ - Struct Device — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Struct Device — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
- v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
diff --git a/docs/_cpp_api/structtorch__tensorrt_1_1GraphInputs.html b/docs/_cpp_api/structtorch__tensorrt_1_1GraphInputs.html index 8353f78ada..2dbc7ae7e4 100644 --- a/docs/_cpp_api/structtorch__tensorrt_1_1GraphInputs.html +++ b/docs/_cpp_api/structtorch__tensorrt_1_1GraphInputs.html @@ -10,7 +10,7 @@ - Struct GraphInputs — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Struct GraphInputs — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
- v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
diff --git a/docs/_cpp_api/structtorch__tensorrt_1_1Input.html b/docs/_cpp_api/structtorch__tensorrt_1_1Input.html index 776e941e27..56d80ca4f9 100644 --- a/docs/_cpp_api/structtorch__tensorrt_1_1Input.html +++ b/docs/_cpp_api/structtorch__tensorrt_1_1Input.html @@ -10,7 +10,7 @@ - Struct Input — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Struct Input — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
- v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
diff --git a/docs/_cpp_api/structtorch__tensorrt_1_1torchscript_1_1CompileSpec.html b/docs/_cpp_api/structtorch__tensorrt_1_1torchscript_1_1CompileSpec.html index b6519c8581..beb37ce8cc 100644 --- a/docs/_cpp_api/structtorch__tensorrt_1_1torchscript_1_1CompileSpec.html +++ b/docs/_cpp_api/structtorch__tensorrt_1_1torchscript_1_1CompileSpec.html @@ -10,7 +10,7 @@ - Struct CompileSpec — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Struct CompileSpec — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
- v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
diff --git a/docs/_cpp_api/torch_tensort_cpp.html b/docs/_cpp_api/torch_tensort_cpp.html index 37e997359c..0bc37590ab 100644 --- a/docs/_cpp_api/torch_tensort_cpp.html +++ b/docs/_cpp_api/torch_tensort_cpp.html @@ -10,7 +10,7 @@ - Torch-TensorRT C++ API — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Torch-TensorRT C++ API — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -275,7 +275,7 @@
- v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
@@ -474,7 +474,7 @@

Class Hierarchy
    • diff --git a/docs/_cpp_api/unabridged_orphan.html b/docs/_cpp_api/unabridged_orphan.html index 14ca9fa802..cd9c776923 100644 --- a/docs/_cpp_api/unabridged_orphan.html +++ b/docs/_cpp_api/unabridged_orphan.html @@ -10,7 +10,7 @@ - Full API — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Full API — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -273,7 +273,7 @@
    - v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
    diff --git a/docs/_downloads/06a1dddfb8c2b5515b697700d863a453/engine_caching_bert_example.ipynb b/docs/_downloads/06a1dddfb8c2b5515b697700d863a453/engine_caching_bert_example.ipynb index 677495750d..c1c3e52e0b 100644 --- a/docs/_downloads/06a1dddfb8c2b5515b697700d863a453/engine_caching_bert_example.ipynb +++ b/docs/_downloads/06a1dddfb8c2b5515b697700d863a453/engine_caching_bert_example.ipynb @@ -15,7 +15,7 @@ }, "outputs": [], "source": [ - "import numpy as np\nimport torch\nimport torch_tensorrt\nfrom engine_caching_example import remove_timing_cache\nfrom transformers import BertModel\n\nnp.random.seed(0)\ntorch.manual_seed(0)\n\nmodel = BertModel.from_pretrained(\"bert-base-uncased\", return_dict=False).cuda().eval()\ninputs = [\n torch.randint(0, 2, (1, 14), dtype=torch.int32).to(\"cuda\"),\n torch.randint(0, 2, (1, 14), dtype=torch.int32).to(\"cuda\"),\n]\n\n\ndef compile_bert(iterations=3):\n times = []\n start = torch.cuda.Event(enable_timing=True)\n end = torch.cuda.Event(enable_timing=True)\n\n # The 1st iteration is to measure the compilation time without engine caching\n # The 2nd and 3rd iterations are to measure the compilation time with engine caching.\n # Since the 2nd iteration needs to compile and save the engine, it will be slower than the 1st iteration.\n # The 3rd iteration should be faster than the 1st iteration because it loads the cached engine.\n for i in range(iterations):\n # remove timing cache and reset dynamo for engine caching messurement\n remove_timing_cache()\n torch._dynamo.reset()\n\n if i == 0:\n cache_built_engines = False\n reuse_cached_engines = False\n else:\n cache_built_engines = True\n reuse_cached_engines = True\n\n start.record()\n compilation_kwargs = {\n \"use_python_runtime\": False,\n \"enabled_precisions\": {torch.float},\n \"truncate_double\": True,\n \"debug\": False,\n \"min_block_size\": 1,\n \"make_refittable\": True,\n \"cache_built_engines\": cache_built_engines,\n \"reuse_cached_engines\": reuse_cached_engines,\n \"engine_cache_dir\": \"/tmp/torch_trt_bert_engine_cache\",\n \"engine_cache_size\": 1 << 30, # 1GB\n }\n optimized_model = torch.compile(\n model,\n backend=\"torch_tensorrt\",\n options=compilation_kwargs,\n )\n optimized_model(*inputs)\n end.record()\n torch.cuda.synchronize()\n times.append(start.elapsed_time(end))\n\n print(\"-----compile bert-----> compilation time:\\n\", times, \"milliseconds\")\n\n\nif __name__ == \"__main__\":\n compile_bert()" + "import numpy as np\nimport torch\nimport torch_tensorrt\nfrom engine_caching_example import remove_timing_cache\nfrom transformers import BertModel\n\nnp.random.seed(0)\ntorch.manual_seed(0)\n\nmodel = BertModel.from_pretrained(\"bert-base-uncased\", return_dict=False).cuda().eval()\ninputs = [\n torch.randint(0, 2, (1, 14), dtype=torch.int32).to(\"cuda\"),\n torch.randint(0, 2, (1, 14), dtype=torch.int32).to(\"cuda\"),\n]\n\n\ndef compile_bert(iterations=3):\n times = []\n start = torch.cuda.Event(enable_timing=True)\n end = torch.cuda.Event(enable_timing=True)\n\n # The 1st iteration is to measure the compilation time without engine caching\n # The 2nd and 3rd iterations are to measure the compilation time with engine caching.\n # Since the 2nd iteration needs to compile and save the engine, it will be slower than the 1st iteration.\n # The 3rd iteration should be faster than the 1st iteration because it loads the cached engine.\n for i in range(iterations):\n # remove timing cache and reset dynamo for engine caching messurement\n remove_timing_cache()\n torch._dynamo.reset()\n\n if i == 0:\n cache_built_engines = False\n reuse_cached_engines = False\n else:\n cache_built_engines = True\n reuse_cached_engines = True\n\n start.record()\n compilation_kwargs = {\n \"use_python_runtime\": False,\n \"enabled_precisions\": {torch.float},\n \"truncate_double\": True,\n \"debug\": False,\n \"min_block_size\": 1,\n \"immutable_weights\": False,\n \"cache_built_engines\": cache_built_engines,\n \"reuse_cached_engines\": reuse_cached_engines,\n \"engine_cache_dir\": \"/tmp/torch_trt_bert_engine_cache\",\n \"engine_cache_size\": 1 << 30, # 1GB\n }\n optimized_model = torch.compile(\n model,\n backend=\"torch_tensorrt\",\n options=compilation_kwargs,\n )\n optimized_model(*inputs)\n end.record()\n torch.cuda.synchronize()\n times.append(start.elapsed_time(end))\n\n print(\"-----compile bert-----> compilation time:\\n\", times, \"milliseconds\")\n\n\nif __name__ == \"__main__\":\n compile_bert()" ] } ], diff --git a/docs/_downloads/1c759c0181fe2845e5579cc82e5b7a7a/engine_caching_example.py b/docs/_downloads/1c759c0181fe2845e5579cc82e5b7a7a/engine_caching_example.py index 28ff73aa72..fb4c341077 100644 --- a/docs/_downloads/1c759c0181fe2845e5579cc82e5b7a7a/engine_caching_example.py +++ b/docs/_downloads/1c759c0181fe2845e5579cc82e5b7a7a/engine_caching_example.py @@ -63,7 +63,7 @@ def remove_timing_cache(path=TIMING_CACHE_PATH): # in a subsequent compilation, either as part of this session or a new session, the cache will # pull the built engine and **refit** the weights which can reduce compilation times by orders of magnitude. # As such, in order to insert a new engine into the cache (i.e. ``cache_built_engines=True``), -# the engine must be refittable (``make_refittable=True``). See :ref:`refit_engine_example` for more details. +# the engine must be refittable (``immutable_weights=False``). See :ref:`refit_engine_example` for more details. def torch_compile(iterations=3): @@ -97,7 +97,7 @@ def torch_compile(iterations=3): "enabled_precisions": enabled_precisions, "debug": debug, "min_block_size": min_block_size, - "make_refittable": True, + "immutable_weights": False, "cache_built_engines": cache_built_engines, "reuse_cached_engines": reuse_cached_engines, }, @@ -157,7 +157,7 @@ def dynamo_compile(iterations=3): enabled_precisions=enabled_precisions, debug=debug, min_block_size=min_block_size, - make_refittable=True, + immutable_weights=False, cache_built_engines=cache_built_engines, reuse_cached_engines=reuse_cached_engines, engine_cache_size=1 << 30, # 1GB @@ -268,7 +268,7 @@ def torch_compile_my_cache(iterations=3): "enabled_precisions": enabled_precisions, "debug": debug, "min_block_size": min_block_size, - "make_refittable": True, + "immutable_weights": False, "cache_built_engines": cache_built_engines, "reuse_cached_engines": reuse_cached_engines, "custom_engine_cache": engine_cache, diff --git a/docs/_downloads/2fbbf7380f818b1cbce2b90bbcaf2904/mutable_torchtrt_module_example.py b/docs/_downloads/2fbbf7380f818b1cbce2b90bbcaf2904/mutable_torchtrt_module_example.py index b68c9a11ee..8b62855c32 100644 --- a/docs/_downloads/2fbbf7380f818b1cbce2b90bbcaf2904/mutable_torchtrt_module_example.py +++ b/docs/_downloads/2fbbf7380f818b1cbce2b90bbcaf2904/mutable_torchtrt_module_example.py @@ -31,7 +31,7 @@ settings = { "use_python": False, "enabled_precisions": {torch.float32}, - "make_refittable": True, + "immutable_weights": False, } model = models.resnet18(pretrained=True).eval().to("cuda") @@ -80,7 +80,7 @@ "use_python_runtime": True, "enabled_precisions": {torch.float16}, "debug": True, - "make_refittable": True, + "immutable_weights": False, } model_id = "runwayml/stable-diffusion-v1-5" diff --git a/docs/_downloads/3454ee6d4b68e83cdf0c757f0059986b/engine_caching_example.ipynb b/docs/_downloads/3454ee6d4b68e83cdf0c757f0059986b/engine_caching_example.ipynb index 7a8fb2b6ac..5837a9094d 100644 --- a/docs/_downloads/3454ee6d4b68e83cdf0c757f0059986b/engine_caching_example.ipynb +++ b/docs/_downloads/3454ee6d4b68e83cdf0c757f0059986b/engine_caching_example.ipynb @@ -22,7 +22,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Engine Caching for JIT Compilation\n\nThe primary goal of engine caching is to help speed up JIT workflows. ``torch.compile``\nprovides a great deal of flexibility in model construction which makes it a good\nfirst tool to try when looking to speed up your workflow. However, historically\nthe cost of compilation and in particular recompilation has been a barrier to entry\nfor many users. If for some reason a subgraph gets invalidated, that graph is reconstructed\nscratch prior to the addition of engine caching. Now as engines are constructed, with ``cache_built_engines=True``,\nengines are saved to disk tied to a hash of their corresponding PyTorch subgraph. If\nin a subsequent compilation, either as part of this session or a new session, the cache will\npull the built engine and **refit** the weights which can reduce compilation times by orders of magnitude.\nAs such, in order to insert a new engine into the cache (i.e. ``cache_built_engines=True``),\nthe engine must be refittable (``make_refittable=True``). See `refit_engine_example` for more details.\n\n" + "## Engine Caching for JIT Compilation\n\nThe primary goal of engine caching is to help speed up JIT workflows. ``torch.compile``\nprovides a great deal of flexibility in model construction which makes it a good\nfirst tool to try when looking to speed up your workflow. However, historically\nthe cost of compilation and in particular recompilation has been a barrier to entry\nfor many users. If for some reason a subgraph gets invalidated, that graph is reconstructed\nscratch prior to the addition of engine caching. Now as engines are constructed, with ``cache_built_engines=True``,\nengines are saved to disk tied to a hash of their corresponding PyTorch subgraph. If\nin a subsequent compilation, either as part of this session or a new session, the cache will\npull the built engine and **refit** the weights which can reduce compilation times by orders of magnitude.\nAs such, in order to insert a new engine into the cache (i.e. ``cache_built_engines=True``),\nthe engine must be refittable (``immutable_weights=False``). See `refit_engine_example` for more details.\n\n" ] }, { @@ -33,7 +33,7 @@ }, "outputs": [], "source": [ - "def torch_compile(iterations=3):\n times = []\n start = torch.cuda.Event(enable_timing=True)\n end = torch.cuda.Event(enable_timing=True)\n\n # The 1st iteration is to measure the compilation time without engine caching\n # The 2nd and 3rd iterations are to measure the compilation time with engine caching.\n # Since the 2nd iteration needs to compile and save the engine, it will be slower than the 1st iteration.\n # The 3rd iteration should be faster than the 1st iteration because it loads the cached engine.\n for i in range(iterations):\n inputs = [torch.rand((100, 3, 224, 224)).to(\"cuda\")]\n # remove timing cache and reset dynamo just for engine caching messurement\n remove_timing_cache()\n torch._dynamo.reset()\n\n if i == 0:\n cache_built_engines = False\n reuse_cached_engines = False\n else:\n cache_built_engines = True\n reuse_cached_engines = True\n\n start.record()\n compiled_model = torch.compile(\n model,\n backend=\"tensorrt\",\n options={\n \"use_python_runtime\": True,\n \"enabled_precisions\": enabled_precisions,\n \"debug\": debug,\n \"min_block_size\": min_block_size,\n \"make_refittable\": True,\n \"cache_built_engines\": cache_built_engines,\n \"reuse_cached_engines\": reuse_cached_engines,\n },\n )\n compiled_model(*inputs) # trigger the compilation\n end.record()\n torch.cuda.synchronize()\n times.append(start.elapsed_time(end))\n\n print(\"----------------torch_compile----------------\")\n print(\"disable engine caching, used:\", times[0], \"ms\")\n print(\"enable engine caching to cache engines, used:\", times[1], \"ms\")\n print(\"enable engine caching to reuse engines, used:\", times[2], \"ms\")\n\n\ntorch_compile()" + "def torch_compile(iterations=3):\n times = []\n start = torch.cuda.Event(enable_timing=True)\n end = torch.cuda.Event(enable_timing=True)\n\n # The 1st iteration is to measure the compilation time without engine caching\n # The 2nd and 3rd iterations are to measure the compilation time with engine caching.\n # Since the 2nd iteration needs to compile and save the engine, it will be slower than the 1st iteration.\n # The 3rd iteration should be faster than the 1st iteration because it loads the cached engine.\n for i in range(iterations):\n inputs = [torch.rand((100, 3, 224, 224)).to(\"cuda\")]\n # remove timing cache and reset dynamo just for engine caching messurement\n remove_timing_cache()\n torch._dynamo.reset()\n\n if i == 0:\n cache_built_engines = False\n reuse_cached_engines = False\n else:\n cache_built_engines = True\n reuse_cached_engines = True\n\n start.record()\n compiled_model = torch.compile(\n model,\n backend=\"tensorrt\",\n options={\n \"use_python_runtime\": True,\n \"enabled_precisions\": enabled_precisions,\n \"debug\": debug,\n \"min_block_size\": min_block_size,\n \"immutable_weights\": False,\n \"cache_built_engines\": cache_built_engines,\n \"reuse_cached_engines\": reuse_cached_engines,\n },\n )\n compiled_model(*inputs) # trigger the compilation\n end.record()\n torch.cuda.synchronize()\n times.append(start.elapsed_time(end))\n\n print(\"----------------torch_compile----------------\")\n print(\"disable engine caching, used:\", times[0], \"ms\")\n print(\"enable engine caching to cache engines, used:\", times[1], \"ms\")\n print(\"enable engine caching to reuse engines, used:\", times[2], \"ms\")\n\n\ntorch_compile()" ] }, { @@ -51,7 +51,7 @@ }, "outputs": [], "source": [ - "def dynamo_compile(iterations=3):\n times = []\n start = torch.cuda.Event(enable_timing=True)\n end = torch.cuda.Event(enable_timing=True)\n\n example_inputs = (torch.randn((100, 3, 224, 224)).to(\"cuda\"),)\n # Mark the dim0 of inputs as dynamic\n batch = torch.export.Dim(\"batch\", min=1, max=200)\n exp_program = torch.export.export(\n model, args=example_inputs, dynamic_shapes={\"x\": {0: batch}}\n )\n\n # The 1st iteration is to measure the compilation time without engine caching\n # The 2nd and 3rd iterations are to measure the compilation time with engine caching.\n # Since the 2nd iteration needs to compile and save the engine, it will be slower than the 1st iteration.\n # The 3rd iteration should be faster than the 1st iteration because it loads the cached engine.\n for i in range(iterations):\n inputs = [torch.rand((100 + i, 3, 224, 224)).to(\"cuda\")]\n remove_timing_cache() # remove timing cache just for engine caching messurement\n if i == 0:\n cache_built_engines = False\n reuse_cached_engines = False\n else:\n cache_built_engines = True\n reuse_cached_engines = True\n\n start.record()\n trt_gm = torch_trt.dynamo.compile(\n exp_program,\n tuple(inputs),\n use_python_runtime=use_python_runtime,\n enabled_precisions=enabled_precisions,\n debug=debug,\n min_block_size=min_block_size,\n make_refittable=True,\n cache_built_engines=cache_built_engines,\n reuse_cached_engines=reuse_cached_engines,\n engine_cache_size=1 << 30, # 1GB\n )\n # output = trt_gm(*inputs)\n end.record()\n torch.cuda.synchronize()\n times.append(start.elapsed_time(end))\n\n print(\"----------------dynamo_compile----------------\")\n print(\"disable engine caching, used:\", times[0], \"ms\")\n print(\"enable engine caching to cache engines, used:\", times[1], \"ms\")\n print(\"enable engine caching to reuse engines, used:\", times[2], \"ms\")\n\n\ndynamo_compile()" + "def dynamo_compile(iterations=3):\n times = []\n start = torch.cuda.Event(enable_timing=True)\n end = torch.cuda.Event(enable_timing=True)\n\n example_inputs = (torch.randn((100, 3, 224, 224)).to(\"cuda\"),)\n # Mark the dim0 of inputs as dynamic\n batch = torch.export.Dim(\"batch\", min=1, max=200)\n exp_program = torch.export.export(\n model, args=example_inputs, dynamic_shapes={\"x\": {0: batch}}\n )\n\n # The 1st iteration is to measure the compilation time without engine caching\n # The 2nd and 3rd iterations are to measure the compilation time with engine caching.\n # Since the 2nd iteration needs to compile and save the engine, it will be slower than the 1st iteration.\n # The 3rd iteration should be faster than the 1st iteration because it loads the cached engine.\n for i in range(iterations):\n inputs = [torch.rand((100 + i, 3, 224, 224)).to(\"cuda\")]\n remove_timing_cache() # remove timing cache just for engine caching messurement\n if i == 0:\n cache_built_engines = False\n reuse_cached_engines = False\n else:\n cache_built_engines = True\n reuse_cached_engines = True\n\n start.record()\n trt_gm = torch_trt.dynamo.compile(\n exp_program,\n tuple(inputs),\n use_python_runtime=use_python_runtime,\n enabled_precisions=enabled_precisions,\n debug=debug,\n min_block_size=min_block_size,\n immutable_weights=False,\n cache_built_engines=cache_built_engines,\n reuse_cached_engines=reuse_cached_engines,\n engine_cache_size=1 << 30, # 1GB\n )\n # output = trt_gm(*inputs)\n end.record()\n torch.cuda.synchronize()\n times.append(start.elapsed_time(end))\n\n print(\"----------------dynamo_compile----------------\")\n print(\"disable engine caching, used:\", times[0], \"ms\")\n print(\"enable engine caching to cache engines, used:\", times[1], \"ms\")\n print(\"enable engine caching to reuse engines, used:\", times[2], \"ms\")\n\n\ndynamo_compile()" ] }, { @@ -69,7 +69,7 @@ }, "outputs": [], "source": [ - "class RAMEngineCache(BaseEngineCache):\n def __init__(\n self,\n ) -> None:\n \"\"\"\n Constructs a user held engine cache in memory.\n \"\"\"\n self.engine_cache: Dict[str, bytes] = {}\n\n def save(\n self,\n hash: str,\n blob: bytes,\n ):\n \"\"\"\n Insert the engine blob to the cache.\n\n Args:\n hash (str): The hash key to associate with the engine blob.\n blob (bytes): The engine blob to be saved.\n\n Returns:\n None\n \"\"\"\n self.engine_cache[hash] = blob\n\n def load(self, hash: str) -> Optional[bytes]:\n \"\"\"\n Load the engine blob from the cache.\n\n Args:\n hash (str): The hash key of the engine to load.\n\n Returns:\n Optional[bytes]: The engine blob if found, None otherwise.\n \"\"\"\n if hash in self.engine_cache:\n return self.engine_cache[hash]\n else:\n return None\n\n\ndef torch_compile_my_cache(iterations=3):\n times = []\n engine_cache = RAMEngineCache()\n start = torch.cuda.Event(enable_timing=True)\n end = torch.cuda.Event(enable_timing=True)\n\n # The 1st iteration is to measure the compilation time without engine caching\n # The 2nd and 3rd iterations are to measure the compilation time with engine caching.\n # Since the 2nd iteration needs to compile and save the engine, it will be slower than the 1st iteration.\n # The 3rd iteration should be faster than the 1st iteration because it loads the cached engine.\n for i in range(iterations):\n inputs = [torch.rand((100, 3, 224, 224)).to(\"cuda\")]\n # remove timing cache and reset dynamo just for engine caching messurement\n remove_timing_cache()\n torch._dynamo.reset()\n\n if i == 0:\n cache_built_engines = False\n reuse_cached_engines = False\n else:\n cache_built_engines = True\n reuse_cached_engines = True\n\n start.record()\n compiled_model = torch.compile(\n model,\n backend=\"tensorrt\",\n options={\n \"use_python_runtime\": True,\n \"enabled_precisions\": enabled_precisions,\n \"debug\": debug,\n \"min_block_size\": min_block_size,\n \"make_refittable\": True,\n \"cache_built_engines\": cache_built_engines,\n \"reuse_cached_engines\": reuse_cached_engines,\n \"custom_engine_cache\": engine_cache,\n },\n )\n compiled_model(*inputs) # trigger the compilation\n end.record()\n torch.cuda.synchronize()\n times.append(start.elapsed_time(end))\n\n print(\"----------------torch_compile----------------\")\n print(\"disable engine caching, used:\", times[0], \"ms\")\n print(\"enable engine caching to cache engines, used:\", times[1], \"ms\")\n print(\"enable engine caching to reuse engines, used:\", times[2], \"ms\")\n\n\ntorch_compile_my_cache()" + "class RAMEngineCache(BaseEngineCache):\n def __init__(\n self,\n ) -> None:\n \"\"\"\n Constructs a user held engine cache in memory.\n \"\"\"\n self.engine_cache: Dict[str, bytes] = {}\n\n def save(\n self,\n hash: str,\n blob: bytes,\n ):\n \"\"\"\n Insert the engine blob to the cache.\n\n Args:\n hash (str): The hash key to associate with the engine blob.\n blob (bytes): The engine blob to be saved.\n\n Returns:\n None\n \"\"\"\n self.engine_cache[hash] = blob\n\n def load(self, hash: str) -> Optional[bytes]:\n \"\"\"\n Load the engine blob from the cache.\n\n Args:\n hash (str): The hash key of the engine to load.\n\n Returns:\n Optional[bytes]: The engine blob if found, None otherwise.\n \"\"\"\n if hash in self.engine_cache:\n return self.engine_cache[hash]\n else:\n return None\n\n\ndef torch_compile_my_cache(iterations=3):\n times = []\n engine_cache = RAMEngineCache()\n start = torch.cuda.Event(enable_timing=True)\n end = torch.cuda.Event(enable_timing=True)\n\n # The 1st iteration is to measure the compilation time without engine caching\n # The 2nd and 3rd iterations are to measure the compilation time with engine caching.\n # Since the 2nd iteration needs to compile and save the engine, it will be slower than the 1st iteration.\n # The 3rd iteration should be faster than the 1st iteration because it loads the cached engine.\n for i in range(iterations):\n inputs = [torch.rand((100, 3, 224, 224)).to(\"cuda\")]\n # remove timing cache and reset dynamo just for engine caching messurement\n remove_timing_cache()\n torch._dynamo.reset()\n\n if i == 0:\n cache_built_engines = False\n reuse_cached_engines = False\n else:\n cache_built_engines = True\n reuse_cached_engines = True\n\n start.record()\n compiled_model = torch.compile(\n model,\n backend=\"tensorrt\",\n options={\n \"use_python_runtime\": True,\n \"enabled_precisions\": enabled_precisions,\n \"debug\": debug,\n \"min_block_size\": min_block_size,\n \"immutable_weights\": False,\n \"cache_built_engines\": cache_built_engines,\n \"reuse_cached_engines\": reuse_cached_engines,\n \"custom_engine_cache\": engine_cache,\n },\n )\n compiled_model(*inputs) # trigger the compilation\n end.record()\n torch.cuda.synchronize()\n times.append(start.elapsed_time(end))\n\n print(\"----------------torch_compile----------------\")\n print(\"disable engine caching, used:\", times[0], \"ms\")\n print(\"enable engine caching to cache engines, used:\", times[1], \"ms\")\n print(\"enable engine caching to reuse engines, used:\", times[2], \"ms\")\n\n\ntorch_compile_my_cache()" ] } ], diff --git a/docs/_downloads/68b8589f80a47518afd92bbad3fda19d/mutable_torchtrt_module_example.ipynb b/docs/_downloads/68b8589f80a47518afd92bbad3fda19d/mutable_torchtrt_module_example.ipynb index f2d5458fc6..065a3d7d44 100644 --- a/docs/_downloads/68b8589f80a47518afd92bbad3fda19d/mutable_torchtrt_module_example.ipynb +++ b/docs/_downloads/68b8589f80a47518afd92bbad3fda19d/mutable_torchtrt_module_example.ipynb @@ -33,7 +33,7 @@ }, "outputs": [], "source": [ - "settings = {\n \"use_python\": False,\n \"enabled_precisions\": {torch.float32},\n \"make_refittable\": True,\n}\n\nmodel = models.resnet18(pretrained=True).eval().to(\"cuda\")\nmutable_module = torch_trt.MutableTorchTensorRTModule(model, **settings)\n# You can use the mutable module just like the original pytorch module. The compilation happens while you first call the mutable module.\nmutable_module(*inputs)" + "settings = {\n \"use_python\": False,\n \"enabled_precisions\": {torch.float32},\n \"immutable_weights\": False,\n}\n\nmodel = models.resnet18(pretrained=True).eval().to(\"cuda\")\nmutable_module = torch_trt.MutableTorchTensorRTModule(model, **settings)\n# You can use the mutable module just like the original pytorch module. The compilation happens while you first call the mutable module.\nmutable_module(*inputs)" ] }, { @@ -94,7 +94,7 @@ }, "outputs": [], "source": [ - "# The LoRA checkpoint is from https://civitai.com/models/12597/moxin\n\nfrom diffusers import DiffusionPipeline\n\nwith torch.no_grad():\n settings = {\n \"use_python_runtime\": True,\n \"enabled_precisions\": {torch.float16},\n \"debug\": True,\n \"make_refittable\": True,\n }\n\n model_id = \"runwayml/stable-diffusion-v1-5\"\n device = \"cuda:0\"\n\n prompt = \"house in forest, shuimobysim, wuchangshuo, best quality\"\n negative = \"(worst quality:2), (low quality:2), (normal quality:2), lowres, normal quality, out of focus, cloudy, (watermark:2),\"\n\n pipe = DiffusionPipeline.from_pretrained(\n model_id, revision=\"fp16\", torch_dtype=torch.float16\n )\n pipe.to(device)\n\n # The only extra line you need\n pipe.unet = torch_trt.MutableTorchTensorRTModule(pipe.unet, **settings)\n\n image = pipe(prompt, negative_prompt=negative, num_inference_steps=30).images[0]\n image.save(\"./without_LoRA_mutable.jpg\")\n\n # Standard Huggingface LoRA loading procedure\n pipe.load_lora_weights(\n \"stablediffusionapi/load_lora_embeddings\",\n weight_name=\"moxin.safetensors\",\n adapter_name=\"lora1\",\n )\n pipe.set_adapters([\"lora1\"], adapter_weights=[1])\n pipe.fuse_lora()\n pipe.unload_lora_weights()\n\n # Refit triggered\n image = pipe(prompt, negative_prompt=negative, num_inference_steps=30).images[0]\n image.save(\"./with_LoRA_mutable.jpg\")" + "# The LoRA checkpoint is from https://civitai.com/models/12597/moxin\n\nfrom diffusers import DiffusionPipeline\n\nwith torch.no_grad():\n settings = {\n \"use_python_runtime\": True,\n \"enabled_precisions\": {torch.float16},\n \"debug\": True,\n \"immutable_weights\": False,\n }\n\n model_id = \"runwayml/stable-diffusion-v1-5\"\n device = \"cuda:0\"\n\n prompt = \"house in forest, shuimobysim, wuchangshuo, best quality\"\n negative = \"(worst quality:2), (low quality:2), (normal quality:2), lowres, normal quality, out of focus, cloudy, (watermark:2),\"\n\n pipe = DiffusionPipeline.from_pretrained(\n model_id, revision=\"fp16\", torch_dtype=torch.float16\n )\n pipe.to(device)\n\n # The only extra line you need\n pipe.unet = torch_trt.MutableTorchTensorRTModule(pipe.unet, **settings)\n\n image = pipe(prompt, negative_prompt=negative, num_inference_steps=30).images[0]\n image.save(\"./without_LoRA_mutable.jpg\")\n\n # Standard Huggingface LoRA loading procedure\n pipe.load_lora_weights(\n \"stablediffusionapi/load_lora_embeddings\",\n weight_name=\"moxin.safetensors\",\n adapter_name=\"lora1\",\n )\n pipe.set_adapters([\"lora1\"], adapter_weights=[1])\n pipe.fuse_lora()\n pipe.unload_lora_weights()\n\n # Refit triggered\n image = pipe(prompt, negative_prompt=negative, num_inference_steps=30).images[0]\n image.save(\"./with_LoRA_mutable.jpg\")" ] } ], diff --git a/docs/_downloads/6a6052d9668b2cb8332d349d328e21c1/_rendered_examples_jupyter.zip b/docs/_downloads/6a6052d9668b2cb8332d349d328e21c1/_rendered_examples_jupyter.zip index 4b93cd71127df2ff50a686cc08c4f2902f1ebe25..2b8400fd47ea441e6f7f5e42ddbfefab6953c450 100644 GIT binary patch delta 973 zcmezMkA3QYcAfxlW)=|!5IEYik*AZB>1fa9>731cAX-LZGC%Lpo}S3xJy9CJr5PB0 zZ{DNM i7n_F6vn3R(mU!Izoo>5Yqpiq*LSfY?wtWcab>Q@r`T!E0tQ z48^u!xwj_Yz;--!_7?@&WfrL@Dh#q~g~#MiB|HoaAgsZ_F#W?nM)B$Oe;9=(`&DOe z{+H*;E{I{|xzxBi{2?mB)o29E~uq$Awj#08w0J$MmCnm2pCU0^g zpTlN>W<4%RoGLem^v+-dx$@m)b_o#ueRVe2)hP#g#X$Vx>o1If^!8Y8#=S})hKwHL zSq-p%?lMo!-D$|c0K&=;|EO$N2xsi!#t}5z_a`xGv0?S3#Pki#jBJzh%Pb*`Rb|%O z`!gB8b4p-19URK3I+GukC~n_V%orpVehf#*<<7BX#rtAG>Q~(JE{AHA3{53uIFQYDqI|s;RNFoa)4MAM1e~dEB3EYg+^SBw+;HLM2MCJ7ur|ar5ifadWGct)V z!}3~BBwE6NJ9A0nyXo)#F&cq`=B$BfjzS>=0|+a@m4JNmV!Hi*MpHJAUyMLu09$8X ARR910 delta 911 zcmbRGpZ(WAcAfxlW)=|!5U7^j$kWNmR4u!CI%hK24!IGRdZ zphT)pOy2Z)O^gzo`Au(ut$FS2FAB2GCQ?xpY#pz+z?woH28P1TS$U7yd5{g6{H|1H zx>hEm<@EGSM%&Hr$~0NPTCSxpvzj8oz%XUAO7#qOS!69h7se=ADL}2Rjmevw$mg(G zrdf|m47;+;$-Oh!Ko0slnOy=zv#rSnJFxg5uNa8mbp3@fklvod&A3+y#L(7bJgXrH z3aO|Wj3?F_GBAL!^5ncc$?Zzvj5E1~(QE<*#P*9xj9P5yzLT1skip2d9q7eEF08sX z7BiL#VAll-m@0_=t1XPOEFh0nGK1Tv7#MNU8Wn^Amna-@iMfHxzP2s13z^hCnr3m9h_;IsrG zmNfcKZ~Vh(t^f)dcnkq!Ne4v{OZ8;UYQ5?Ie>3vPgH*<7o^v}S&cFb|nkXtCO*j0@ zXaRCl_FteAUr+D&%cu+1lbW)`{5^;R{R4xLSXvQe~hYNttgR?qV;|l hP-K?G zP;3j5OV#0;oaZaCd9w0DZje=F`l37_y4QLV57BclnYAcp?Q4@*TRd-)1)59emQ z!iV3C=|D3|r~6AWvTZ*v#mLJ9bny0jGK?xIK*n^IM#c~j9o5L_3!+yxGDf2&f$4%x zjP~*%&n2DD@;J-QzyQKJ;3NbgmNXVj&u?P12I*hZ#3;kmZauxAiBWv=ZEL>i@0%F; z6+pV-5e$rERTSOQ9+M3{)ThsBX5<0egBr64rAr!TOfP6=v;f(&su^g{-z2a-)9*Jk z%7O&{0R+Z&B!Fe49gBZksDow z)Xu9hFo3W;iiUU7*S9e0fh@V-0<`4U^gk_(h9ItfE6^b(mnJ)264gOB4kb098ut^2D(+Rm*P9Vg1SuqLX>exrM4_dm{gKSXs>zV_*Pb zIfm)>O^gbg&q#!@tK=qTr^Xkhre&6tBqrsgCMc9-B$g;-7Aq8|mME0uDLPC&%L1Odzz*DTEsA^M{tQ0_YP7Hs?hC^z4TmcKn8Jx*- z{2*Gh$cqm|mo_wm>0fL5PbHVYXL?Qm&_JlNtg;lt~pFgmC+Ey^=buLp?Ya@z$MY?wXmRp$2l - Overview: module code — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + Overview: module code — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -272,7 +272,7 @@
    - v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
    diff --git a/docs/_modules/torch_tensorrt/_Device.html b/docs/_modules/torch_tensorrt/_Device.html index b815e03a65..bc124f5f0d 100644 --- a/docs/_modules/torch_tensorrt/_Device.html +++ b/docs/_modules/torch_tensorrt/_Device.html @@ -9,7 +9,7 @@ - torch_tensorrt._Device — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + torch_tensorrt._Device — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -272,7 +272,7 @@
    - v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
    diff --git a/docs/_modules/torch_tensorrt/_Input.html b/docs/_modules/torch_tensorrt/_Input.html index 3ca82ad497..c5857e3ddc 100644 --- a/docs/_modules/torch_tensorrt/_Input.html +++ b/docs/_modules/torch_tensorrt/_Input.html @@ -9,7 +9,7 @@ - torch_tensorrt._Input — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + torch_tensorrt._Input — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -272,7 +272,7 @@
    - v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
    diff --git a/docs/_modules/torch_tensorrt/_compile.html b/docs/_modules/torch_tensorrt/_compile.html index 4dc84139ca..af0140c064 100644 --- a/docs/_modules/torch_tensorrt/_compile.html +++ b/docs/_modules/torch_tensorrt/_compile.html @@ -9,7 +9,7 @@ - torch_tensorrt._compile — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + torch_tensorrt._compile — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -272,7 +272,7 @@
    - v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
    diff --git a/docs/_modules/torch_tensorrt/_enums.html b/docs/_modules/torch_tensorrt/_enums.html index a98528998b..330f254659 100644 --- a/docs/_modules/torch_tensorrt/_enums.html +++ b/docs/_modules/torch_tensorrt/_enums.html @@ -9,7 +9,7 @@ - torch_tensorrt._enums — Torch-TensorRT v2.6.0.dev0+a945aeb documentation + torch_tensorrt._enums — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation @@ -272,7 +272,7 @@
    - v2.6.0.dev0+a945aeb + v2.6.0.dev0+93b5b8f
    @@ -685,7 +685,7 @@

    Source code for torch_tensorrt._enums

                     return dtype.f32
             elif t == np.float64:
                 return dtype.f64
-            elif t == np.bool:
+            elif t == np.bool_:
                 return dtype.b
             # TODO: Consider using ml_dtypes when issues like this are resolved:
             # https://github.com/pytorch/pytorch/issues/109873
@@ -1849,7 +1849,7 @@ 
    Source code for torch_tensorrt._enums
         def __str__(self) -> str:
         return str(self.name)
 
-    @needs_torch_tensorrt_runtime
+    @needs_torch_tensorrt_runtime  # type: ignore
     def _to_serialized_rt_platform(self) -> str:
         val: str = torch.ops.tensorrt._platform_unknown()
 
diff --git a/docs/_modules/torch_tensorrt/dynamo/_compiler.html b/docs/_modules/torch_tensorrt/dynamo/_compiler.html
index 7c3d2f05f8..bce161f2e6 100644
--- a/docs/_modules/torch_tensorrt/dynamo/_compiler.html
+++ b/docs/_modules/torch_tensorrt/dynamo/_compiler.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.dynamo._compiler — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.dynamo._compiler — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -528,7 +528,6 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
         Set[Union[torch.dtype, dtype]], Tuple[Union[torch.dtype, dtype]]
     ] = _defaults.ENABLED_PRECISIONS,
     engine_capability: EngineCapability = _defaults.ENGINE_CAPABILITY,
-    make_refittable: bool = _defaults.MAKE_REFITTABLE,
     debug: bool = _defaults.DEBUG,
     num_avg_timing_iters: int = _defaults.NUM_AVG_TIMING_ITERS,
     workspace_size: int = _defaults.WORKSPACE_SIZE,
@@ -558,6 +557,9 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
     custom_engine_cache: Optional[BaseEngineCache] = _defaults.CUSTOM_ENGINE_CACHE,
     use_explicit_typing: bool = _defaults.USE_EXPLICIT_TYPING,
     use_fp32_acc: bool = _defaults.USE_FP32_ACC,
+    refit_identical_engine_weights: bool = _defaults.REFIT_IDENTICAL_ENGINE_WEIGHTS,
+    strip_engine_weights: bool = _defaults.STRIP_ENGINE_WEIGHTS,
+    immutable_weights: bool = _defaults.IMMUTABLE_WEIGHTS,
     enable_weight_streaming: bool = _defaults.ENABLE_WEIGHT_STREAMING,
     **kwargs: Any,
 ) -> torch.fx.GraphModule:
@@ -597,7 +599,6 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
         assume_dynamic_shape_support (bool): Setting this to true enables the converters work for both dynamic and static shapes. Default: False
         sparse_weights (bool): Enable sparsity for convolution and fully connected layers.
         enabled_precision (Set(Union(torch.dtype, torch_tensorrt.dtype))): The set of datatypes that TensorRT can use when selecting kernels
-        refit (bool): Enable refitting
         debug (bool): Enable debuggable engine
         capability (torch_tensorrt.EngineCapability): Restrict kernel selection to safe gpu kernels or safe dla kernels
         num_avg_timing_iters (int): Number of averaging timing iterations used to select kernels
@@ -629,6 +630,9 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
         custom_engine_cache (Optional[BaseEngineCache]): Engine cache instance to use for saving and loading engines. Users can provide their own engine cache by inheriting from BaseEngineCache. If used, engine_cache_dir and engine_cache_size will be ignored.
         use_explicit_typing (bool): This flag enables strong typing in TensorRT compilation which respects the precisions set in the Pytorch model. This is useful when users have mixed precision graphs.
         use_fp32_acc (bool): This option inserts cast to FP32 nodes around matmul layers and TensorRT ensures the accumulation of matmul happens in FP32. Use this only when FP16 precision is configured in enabled_precisions.
+        refit_identical_engine_weights (bool): Refit engines with identical weights. This is useful when the same model is compiled multiple times with different inputs and the weights are the same. This will save time by reusing the same engine for different inputs.
+        strip_engine_weights (bool): Strip engine weights from the serialized engine. This is useful when the engine is to be deployed in an environment where the weights are not required.
+        immutable_weights (bool): Build non-refittable engines. This is useful for some layers that are not refittable. If this argument is set to true, `strip_engine_weights` and `refit_identical_engine_weights` will be ignored.
         enable_weight_streaming (bool): Enable weight streaming.
         **kwargs: Any,
     Returns:
@@ -658,14 +662,44 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
 
     if "refit" in kwargs.keys():
         warnings.warn(
-            "Refit is deprecated. Please use make_refittable=True if you want to enable refitting of the engine.",
+            "`refit` is deprecated. Please set `immutable_weights=False` to build a refittable engine whose weights can be refitted.",
             DeprecationWarning,
             stacklevel=2,
         )
-        if make_refittable:
-            raise ValueError("Use flag make_refittable only. Flag refit is deprecated.")
+        if immutable_weights:
+            raise ValueError(
+                "Use flag `immutable_weights` only. Flag `refit` is deprecated."
+            )
         else:
-            make_refittable = kwargs["refit"]
+            immutable_weights = not kwargs["refit"]
+
+    if "make_refittable" in kwargs.keys():
+        warnings.warn(
+            "`make_refittable` is deprecated. Please set `immutable_weights=False` to build a refittable engine whose weights can be refitted",
+            DeprecationWarning,
+            stacklevel=2,
+        )
+        if immutable_weights:
+            raise ValueError(
+                "Use flag `immutable_weights` only. Flag `make_refittable` is deprecated."
+            )
+        else:
+            immutable_weights = not kwargs["make_refittable"]
+
+    if refit_identical_engine_weights:
+        if immutable_weights:
+            raise ValueError(
+                "`immutable_weights` must be False when `refit_identical_engine_weights` is True."
+            )
+
+    if (
+        not immutable_weights
+        and not refit_identical_engine_weights
+        and enable_weight_streaming
+    ):
+        raise ValueError(
+            "TensorRT's `REFIT` flag is not compatible with `enable_weight_streaming=True` for now. This issue was reported on https://github.com/pytorch/TensorRT/issues/3305"
+        )
 
     engine_capability = EngineCapability._from(engine_capability)
 
@@ -740,7 +774,6 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
         "require_full_compilation": require_full_compilation,
         "disable_tf32": disable_tf32,
         "sparse_weights": sparse_weights,
-        "make_refittable": make_refittable,
         "engine_capability": engine_capability,
         "dla_sram_size": dla_sram_size,
         "dla_local_dram_size": dla_local_dram_size,
@@ -751,6 +784,9 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
         "lazy_engine_init": lazy_engine_init,
         "cache_built_engines": cache_built_engines,
         "reuse_cached_engines": reuse_cached_engines,
+        "refit_identical_engine_weights": refit_identical_engine_weights,
+        "strip_engine_weights": strip_engine_weights,
+        "immutable_weights": immutable_weights,
         "enable_cross_compile_for_windows": True,
         "enable_weight_streaming": enable_weight_streaming,
     }
@@ -807,7 +843,6 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
         Set[Union[torch.dtype, dtype]], Tuple[Union[torch.dtype, dtype]]
     ] = _defaults.ENABLED_PRECISIONS,
     engine_capability: EngineCapability = _defaults.ENGINE_CAPABILITY,
-    make_refittable: bool = _defaults.MAKE_REFITTABLE,
     debug: bool = _defaults.DEBUG,
     num_avg_timing_iters: int = _defaults.NUM_AVG_TIMING_ITERS,
     workspace_size: int = _defaults.WORKSPACE_SIZE,
@@ -837,6 +872,9 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
     custom_engine_cache: Optional[BaseEngineCache] = _defaults.CUSTOM_ENGINE_CACHE,
     use_explicit_typing: bool = _defaults.USE_EXPLICIT_TYPING,
     use_fp32_acc: bool = _defaults.USE_FP32_ACC,
+    refit_identical_engine_weights: bool = _defaults.REFIT_IDENTICAL_ENGINE_WEIGHTS,
+    strip_engine_weights: bool = _defaults.STRIP_ENGINE_WEIGHTS,
+    immutable_weights: bool = _defaults.IMMUTABLE_WEIGHTS,
     enable_weight_streaming: bool = _defaults.ENABLE_WEIGHT_STREAMING,
     **kwargs: Any,
 ) -> torch.fx.GraphModule:
@@ -878,7 +916,6 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
         assume_dynamic_shape_support (bool): Setting this to true enables the converters work for both dynamic and static shapes. Default: False
         sparse_weights (bool): Enable sparsity for convolution and fully connected layers.
         enabled_precision (Set(Union(torch.dtype, torch_tensorrt.dtype))): The set of datatypes that TensorRT can use when selecting kernels
-        refit (bool): Enable refitting
         debug (bool): Enable debuggable engine
         capability (torch_tensorrt.EngineCapability): Restrict kernel selection to safe gpu kernels or safe dla kernels
         num_avg_timing_iters (int): Number of averaging timing iterations used to select kernels
@@ -910,6 +947,9 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
         custom_engine_cache (Optional[BaseEngineCache]): Engine cache instance to use for saving and loading engines. Users can provide their own engine cache by inheriting from BaseEngineCache. If used, engine_cache_dir and engine_cache_size will be ignored.
         use_explicit_typing (bool): This flag enables strong typing in TensorRT compilation which respects the precisions set in the Pytorch model. This is useful when users have mixed precision graphs.
         use_fp32_acc (bool): This option inserts cast to FP32 nodes around matmul layers and TensorRT ensures the accumulation of matmul happens in FP32. Use this only when FP16 precision is configured in enabled_precisions.
+        refit_identical_engine_weights (bool): Refit engines with identical weights. This is useful when the same model is compiled multiple times with different inputs and the weights are the same. This will save time by reusing the same engine for different inputs.
+        strip_engine_weights (bool): Strip engine weights from the serialized engine. This is useful when the engine is to be deployed in an environment where the weights are not required.
+        immutable_weights (bool): Build non-refittable engines. This is useful for some layers that are not refittable. If this argument is set to true, `strip_engine_weights` and `refit_identical_engine_weights` will be ignored.
         enable_weight_streaming (bool): Enable weight streaming.
         **kwargs: Any,
     Returns:
@@ -933,14 +973,44 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
 
     if "refit" in kwargs.keys():
         warnings.warn(
-            "Refit is deprecated. Please use make_refittable=True if you want to enable refitting of the engine.",
+            "`refit` is deprecated. Please set `immutable_weights=False` to build a refittable engine whose weights can be refitted",
+            DeprecationWarning,
+            stacklevel=2,
+        )
+        if immutable_weights:
+            raise ValueError(
+                "Use flag `immutable_weights` only. Flag `refit` is deprecated."
+            )
+        else:
+            immutable_weights = not kwargs["refit"]
+
+    if "make_refittable" in kwargs.keys():
+        warnings.warn(
+            "`make_refittable` is deprecated. Please set `immutable_weights=False` to build a refittable engine whose weights can be refitted",
             DeprecationWarning,
             stacklevel=2,
         )
-        if make_refittable:
-            raise ValueError("Use flag make_refittable only. Flag refit is deprecated.")
+        if immutable_weights:
+            raise ValueError(
+                "Use flag `immutable_weights` only. Flag `make_refittable` is deprecated."
+            )
         else:
-            make_refittable = kwargs["refit"]
+            immutable_weights = not kwargs["make_refittable"]
+
+    if refit_identical_engine_weights:
+        if immutable_weights:
+            raise ValueError(
+                "`immutable_weights` must be False when `refit_identical_engine_weights` is True."
+            )
+
+    if (
+        not immutable_weights
+        and not refit_identical_engine_weights
+        and enable_weight_streaming
+    ):
+        raise ValueError(
+            "TensorRT's `REFIT` flag is not compatible with `enable_weight_streaming=True` for now. This issue was reported on https://github.com/pytorch/TensorRT/issues/3305"
+        )
 
     if (
         "enable_cross_compile_for_windows" in kwargs.keys()
@@ -1006,9 +1076,6 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
 
     engine_cache = None
     if cache_built_engines or reuse_cached_engines:
-        assert (
-            make_refittable
-        ), "Engine caching requires make_refittable to be set to True"
         engine_cache = (
             custom_engine_cache
             if custom_engine_cache is not None
@@ -1039,7 +1106,6 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
         "require_full_compilation": require_full_compilation,
         "disable_tf32": disable_tf32,
         "sparse_weights": sparse_weights,
-        "make_refittable": make_refittable,
         "engine_capability": engine_capability,
         "dla_sram_size": dla_sram_size,
         "dla_local_dram_size": dla_local_dram_size,
@@ -1052,6 +1118,9 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
         "reuse_cached_engines": reuse_cached_engines,
         "use_explicit_typing": use_explicit_typing,
         "use_fp32_acc": use_fp32_acc,
+        "refit_identical_engine_weights": refit_identical_engine_weights,
+        "strip_engine_weights": strip_engine_weights,
+        "immutable_weights": immutable_weights,
         "enable_cross_compile_for_windows": False,
         "enable_weight_streaming": enable_weight_streaming,
     }
@@ -1326,7 +1395,6 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
     require_full_compilation: bool = _defaults.REQUIRE_FULL_COMPILATION,
     disable_tf32: bool = _defaults.DISABLE_TF32,
     sparse_weights: bool = _defaults.SPARSE_WEIGHTS,
-    make_refittable: bool = _defaults.MAKE_REFITTABLE,
     engine_capability: EngineCapability = _defaults.ENGINE_CAPABILITY,
     num_avg_timing_iters: int = _defaults.NUM_AVG_TIMING_ITERS,
     dla_sram_size: int = _defaults.DLA_SRAM_SIZE,
@@ -1337,6 +1405,9 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
     timing_cache_path: str = _defaults.TIMING_CACHE_PATH,
     use_explicit_typing: bool = _defaults.USE_EXPLICIT_TYPING,
     use_fp32_acc: bool = _defaults.USE_FP32_ACC,
+    refit_identical_engine_weights: bool = _defaults.REFIT_IDENTICAL_ENGINE_WEIGHTS,
+    strip_engine_weights: bool = _defaults.STRIP_ENGINE_WEIGHTS,
+    immutable_weights: bool = _defaults.IMMUTABLE_WEIGHTS,
     enable_weight_streaming: bool = _defaults.ENABLE_WEIGHT_STREAMING,
     **kwargs: Any,
 ) -> bytes:
@@ -1387,7 +1458,6 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
             Only applicable for `ir="dynamo"`; has no effect for `torch.compile` path
         disable_tf32 (bool): Whether to disable TF32 computation for TRT layers
         sparse_weights (bool): Whether to allow the builder to use sparse weights
-        refit (bool): Whether to build a refittable engine
         engine_capability (trt.EngineCapability): Restrict kernel selection to safe gpu kernels or safe dla kernels
         num_avg_timing_iters (int): Number of averaging timing iterations used to select kernels
         dla_sram_size (int): Fast software managed RAM used by DLA to communicate within a layer.
@@ -1398,6 +1468,9 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
         timing_cache_path (str): Path to the timing cache if it exists (or) where it will be saved after compilation
         use_explicit_typing (bool): This flag enables strong typing in TensorRT compilation which respects the precisions set in the Pytorch model. This is useful when users have mixed precision graphs.
         use_fp32_acc (bool): This option inserts cast to FP32 nodes around matmul layers and TensorRT ensures the accumulation of matmul happens in FP32. Use this only when FP16 precision is configured in enabled_precisions.
+        refit_identical_engine_weights (bool): Refit engines with identical weights. This is useful when the same model is compiled multiple times with different inputs and the weights are the same. This will save time by reusing the same engine for different inputs.
+        strip_engine_weights (bool): Strip engine weights from the serialized engine. This is useful when the engine is to be deployed in an environment where the weights are not required.
+        immutable_weights (bool): Build non-refittable engines. This is useful for some layers that are not refittable. If this argument is set to true, `strip_engine_weights` and `refit_identical_engine_weights` will be ignored.
         enable_weight_streaming (bool): Enable weight streaming.
     Returns:
         bytes: Serialized TensorRT engine, can either be saved to a file or deserialized via TensorRT APIs
@@ -1417,12 +1490,48 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
                 DeprecationWarning,
                 stacklevel=2,
             )
+
     if "refit" in kwargs.keys():
         warnings.warn(
-            "Refit is deprecated. Please use make_refittable=True if you want to enable refitting of the engine.",
+            "`refit` is deprecated. Please set `immutable_weights=False` to build a refittable engine whose weights can be refitted",
+            DeprecationWarning,
+            stacklevel=2,
+        )
+        if immutable_weights:
+            raise ValueError(
+                "Use flag `immutable_weights` only. Flag `refit` is deprecated."
+            )
+        else:
+            immutable_weights = not kwargs["refit"]
+
+    if "make_refittable" in kwargs.keys():
+        warnings.warn(
+            "`make_refittable` is deprecated. Please set `immutable_weights=False` to build a refittable engine whose weights can be refitted",
             DeprecationWarning,
             stacklevel=2,
         )
+        if immutable_weights:
+            raise ValueError(
+                "Use flag `immutable_weights` only. Flag `make_refittable` is deprecated."
+            )
+        else:
+            immutable_weights = not kwargs["make_refittable"]
+
+    if refit_identical_engine_weights:
+        if immutable_weights:
+            raise ValueError(
+                "`immutable_weights` must be False when `refit_identical_engine_weights` is True."
+            )
+
+    if (
+        not immutable_weights
+        and not refit_identical_engine_weights
+        and enable_weight_streaming
+    ):
+        raise ValueError(
+            "TensorRT's `REFIT` flag is not compatible with `enable_weight_streaming=True` for now. This issue was reported on https://github.com/pytorch/TensorRT/issues/3305"
+        )
+
     if arg_inputs is None and inputs is None:
         raise AssertionError("'arg_inputs' and 'inputs' should not both be None.")
 
@@ -1465,7 +1574,6 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
         "require_full_compilation": require_full_compilation,
         "disable_tf32": disable_tf32,
         "sparse_weights": sparse_weights,
-        "make_refittable": make_refittable,
         "engine_capability": engine_capability,
         "num_avg_timing_iters": num_avg_timing_iters,
         "dla_sram_size": dla_sram_size,
@@ -1474,6 +1582,9 @@ 
    Source code for torch_tensorrt.dynamo._compiler
    <
         "timing_cache_path": timing_cache_path,
         "use_explicit_typing": use_explicit_typing,
         "use_fp32_acc": use_fp32_acc,
+        "refit_identical_engine_weights": refit_identical_engine_weights,
+        "strip_engine_weights": strip_engine_weights,
+        "immutable_weights": immutable_weights,
         "enable_weight_streaming": enable_weight_streaming,
     }
 
diff --git a/docs/_modules/torch_tensorrt/dynamo/_exporter.html b/docs/_modules/torch_tensorrt/dynamo/_exporter.html
index dcd44d352e..5a67417ea4 100644
--- a/docs/_modules/torch_tensorrt/dynamo/_exporter.html
+++ b/docs/_modules/torch_tensorrt/dynamo/_exporter.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.dynamo._exporter — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.dynamo._exporter — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/_modules/torch_tensorrt/dynamo/_refit.html b/docs/_modules/torch_tensorrt/dynamo/_refit.html
index c0bf8ffcd1..4cb2709f20 100644
--- a/docs/_modules/torch_tensorrt/dynamo/_refit.html
+++ b/docs/_modules/torch_tensorrt/dynamo/_refit.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.dynamo._refit — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.dynamo._refit — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -621,13 +621,26 @@ 
    Source code for torch_tensorrt.dynamo._refit
    if torch_device.type == "cuda"
             else trt.TensorLocation.HOST
         )
+
+        constant_mapping: dict[str, Any] = weight_name_map.pop(
+            "constant_mapping", {}
+        )  # type: ignore
         mapping = construct_refit_mapping_from_weight_name_map(
             weight_name_map, new_gm.state_dict()
         )
+        constant_mapping_with_type = {}
+
+        for constant_name, val in constant_mapping.items():
+            np_weight_type = val.dtype
+            val_tensor = torch.from_numpy(val).cuda()
+            trt_dtype = dtype.try_from(np_weight_type).to(trt.DataType)
+            torch_dtype = dtype.try_from(np_weight_type).to(torch.dtype)
+            constant_mapping_with_type[constant_name] = (
+                val_tensor.clone().reshape(-1).contiguous().to(torch_dtype),
+                trt_dtype,
+            )
 
-        # Debug Use
-        # correct = construct_refit_mapping(new_gm, input_list, settings)
-        # comparison = {k: (np.allclose(correct[k][0], mapping[k][0].cpu().numpy(), 1e-2, 1e-2), correct[k][0], mapping[k][0]) for k in mapping if k in correct}
+        mapping.update(constant_mapping_with_type)
 
         for layer_name in weight_list:
             if layer_name not in mapping:
@@ -716,7 +729,7 @@ 
    Source code for torch_tensorrt.dynamo._refit
    ]
         assert (
             encoded_metadata != ""
-        ), "The engine provided is either not refittable or was built with a version of Torch-TensorRT that is too old, please recompile using the latest version with make_refittable=True"
+        ), "The engine provided is either not refittable or was built with a version of Torch-TensorRT that is too old, please recompile using the latest version"
         settings = TorchTensorRTModule.decode_metadata(encoded_metadata)["settings"]
         # Handle torch modules
         compiled_submodules_map = dict(compiled_submodules)
@@ -734,8 +747,8 @@ 
    Source code for torch_tensorrt.dynamo._refit
    assert settings is not None
 
     assert (
-        settings.make_refittable
-    ), "Refitting is not enabled. Please recompile the engine with refit=True."
+        not settings.immutable_weights
+    ), "Refitting is not enabled. Please recompile the engine with immutable_weights=False."
 
     if settings.debug:
         set_log_level(logger.parent, logging.DEBUG)
@@ -914,17 +927,21 @@ 
    Source code for torch_tensorrt.dynamo._refit
    weight_name_map=None,
                 )
 
-        if isinstance(compiled_submodule, TorchTensorRTModule):
-            serialized_engine = bytes(engine.serialize())
-            new_engine_info = list(engine_info)
-            new_engine_info[ENGINE_IDX] = serialized_engine
-            refitted_engine = torch.classes.tensorrt.Engine(tuple(new_engine_info))
-            compiled_submodule.engine = refitted_engine
+        # clear EXCLUDE_WEIGHTS flag
+        serialization_config = engine.create_serialization_config()
+        serialization_config.clear_flag(trt.SerializationFlag.EXCLUDE_WEIGHTS)
+        serialized_engine = engine.serialize_with_config(serialization_config)
+
+        if isinstance(
+            compiled_submodule, (PythonTorchTensorRTModule, TorchTensorRTModule)
+        ):
+            compiled_submodule.engine = None  # Clear the engine for TorchTensorRTModule, otherwise it won't be updated
+            compiled_submodule.serialized_engine = bytes(serialized_engine)
+            compiled_submodule.setup_engine()
 
         elif inline_module:
-            serialized_engine = bytes(engine.serialize())
             new_engine_info = list(engine_info)
-            new_engine_info[ENGINE_IDX] = serialized_engine
+            new_engine_info[ENGINE_IDX] = bytes(serialized_engine)
             refitted_engine = torch.classes.tensorrt.Engine(tuple(new_engine_info))
             setattr(compiled_module, f"{name}_engine", refitted_engine)
 
diff --git a/docs/_modules/torch_tensorrt/dynamo/_settings.html b/docs/_modules/torch_tensorrt/dynamo/_settings.html
index ef0866e39c..2b001093d2 100644
--- a/docs/_modules/torch_tensorrt/dynamo/_settings.html
+++ b/docs/_modules/torch_tensorrt/dynamo/_settings.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.dynamo._settings — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.dynamo._settings — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -484,16 +484,18 @@ 
    Source code for torch_tensorrt.dynamo._settings
    <
     ENABLED_PRECISIONS,
     ENGINE_CAPABILITY,
     HARDWARE_COMPATIBLE,
+    IMMUTABLE_WEIGHTS,
     LAZY_ENGINE_INIT,
-    MAKE_REFITTABLE,
     MAX_AUX_STREAMS,
     MIN_BLOCK_SIZE,
     NUM_AVG_TIMING_ITERS,
     OPTIMIZATION_LEVEL,
     PASS_THROUGH_BUILD_FAILURES,
+    REFIT_IDENTICAL_ENGINE_WEIGHTS,
     REQUIRE_FULL_COMPILATION,
     REUSE_CACHED_ENGINES,
     SPARSE_WEIGHTS,
+    STRIP_ENGINE_WEIGHTS,
     TIMING_CACHE_PATH,
     TRUNCATE_DOUBLE,
     USE_EXPLICIT_TYPING,
@@ -534,7 +536,6 @@ 
    Source code for torch_tensorrt.dynamo._settings
    <
         assume_dynamic_shape_support (bool): Setting this to true enables the converters work for both dynamic and static shapes. Default: False
         disable_tf32 (bool): Whether to disable TF32 computation for TRT layers
         sparse_weights (bool): Whether to allow the builder to use sparse weights
-        refit (bool): Whether to build a refittable engine
         engine_capability (trt.EngineCapability): Restrict kernel selection to safe gpu kernels or safe dla kernels
         num_avg_timing_iters (int): Number of averaging timing iterations used to select kernels
         dla_sram_size (int): Fast software managed RAM used by DLA to communicate within a layer.
@@ -549,6 +550,9 @@ 
    Source code for torch_tensorrt.dynamo._settings
    <
         reuse_cached_engines (bool): Whether to load the compiled TRT engines from storage
         use_strong_typing (bool): This flag enables strong typing in TensorRT compilation which respects the precisions set in the Pytorch model. This is useful when users have mixed precision graphs.
         use_fp32_acc (bool): This option inserts cast to FP32 nodes around matmul layers and TensorRT ensures the accumulation of matmul happens in FP32. Use this only when FP16 precision is configured in enabled_precisions.
+        refit_identical_engine_weights (bool): Whether to refit the engine with identical weights
+        strip_engine_weights (bool): Whether to strip the engine weights
+        immutable_weights (bool): Build non-refittable engines. This is useful for some layers that are not refittable. If this argument is set to true, `strip_engine_weights` and `refit_identical_engine_weights` will be ignored
         enable_weight_streaming (bool): Enable weight streaming.
         enable_cross_compile_for_windows (bool): By default this is False means TensorRT engines can only be executed on the same platform where they were built.
             True will enable cross-platform compatibility which allows the engine to be built on Linux and run on Windows
@@ -572,7 +576,6 @@ 
    Source code for torch_tensorrt.dynamo._settings
    <
     disable_tf32: bool = DISABLE_TF32
     assume_dynamic_shape_support: bool = ASSUME_DYNAMIC_SHAPE_SUPPORT
     sparse_weights: bool = SPARSE_WEIGHTS
-    make_refittable: bool = MAKE_REFITTABLE
     engine_capability: EngineCapability = field(
         default_factory=lambda: ENGINE_CAPABILITY
     )
@@ -588,6 +591,9 @@ 
    Source code for torch_tensorrt.dynamo._settings
    <
     reuse_cached_engines: bool = REUSE_CACHED_ENGINES
     use_explicit_typing: bool = USE_EXPLICIT_TYPING
     use_fp32_acc: bool = USE_FP32_ACC
+    refit_identical_engine_weights: bool = REFIT_IDENTICAL_ENGINE_WEIGHTS
+    strip_engine_weights: bool = STRIP_ENGINE_WEIGHTS
+    immutable_weights: bool = IMMUTABLE_WEIGHTS
     enable_weight_streaming: bool = ENABLE_WEIGHT_STREAMING
     enable_cross_compile_for_windows: bool = ENABLE_CROSS_COMPILE_FOR_WINDOWS
    
 
@@ -599,9 +605,11 @@ 
    Source code for torch_tensorrt.dynamo._settings
    <
     "optimization_level",
     "disable_tf32",
     "sparse_weights",
-    "make_refittable",
     "engine_capability",
     "hardware_compatible",
+    "refit_identical_engine_weights",
+    "strip_engine_weights",  # TODO: @Evan to remove this after implementing caching weight-stripped engines as default?
+    "immutable_weights",
     "enable_weight_streaming",
 )
 
diff --git a/docs/_modules/torch_tensorrt/dynamo/_tracer.html b/docs/_modules/torch_tensorrt/dynamo/_tracer.html
index 1ed7f46aa2..c38114e003 100644
--- a/docs/_modules/torch_tensorrt/dynamo/_tracer.html
+++ b/docs/_modules/torch_tensorrt/dynamo/_tracer.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.dynamo._tracer — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.dynamo._tracer — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/_modules/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.html b/docs/_modules/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.html
index f007d8e5b4..2cb075db4d 100644
--- a/docs/_modules/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.html
+++ b/docs/_modules/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -530,7 +530,7 @@ 
    Source code for torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModuleUnion[torch.dtype, dtype]
         ] = _defaults.ENABLED_PRECISIONS,
         engine_capability: EngineCapability = _defaults.ENGINE_CAPABILITY,
-        make_refittable: bool = _defaults.MAKE_REFITTABLE,
+        immutable_weights: bool = _defaults.IMMUTABLE_WEIGHTS,
         debug: bool = _defaults.DEBUG,
         num_avg_timing_iters: int = _defaults.NUM_AVG_TIMING_ITERS,
         workspace_size: int = _defaults.WORKSPACE_SIZE,
@@ -568,7 +568,7 @@ 
    Source code for torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule            assume_dynamic_shape_support (bool): Setting this to true enables the converters work for both dynamic and static shapes. Default: False
             sparse_weights (bool): Enable sparsity for convolution and fully connected layers.
             enabled_precision (Set(Union(torch.dtype, torch_tensorrt.dtype))): The set of datatypes that TensorRT can use when selecting kernels
-            refit (bool): Enable refitting
+            immutable_weights (bool): Build non-refittable engines. This is useful for some layers that are not refittable.
             debug (bool): Enable debuggable engine
             capability (torch_tensorrt.EngineCapability): Restrict kernel selection to safe gpu kernels or safe dla kernels
             num_avg_timing_iters (int): Number of averaging timing iterations used to select kernels
@@ -617,8 +617,8 @@ 
    Source code for torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModuledevice = to_torch_tensorrt_device(device)
         enabled_precisions = {dtype._from(p) for p in enabled_precisions}
         assert (
-            make_refittable
-        ), "'make_refittable' has to be True for a MutableTorchTensorRTModule."
+            not immutable_weights
+        ), "`immutable_weights` has to be False for a MutableTorchTensorRTModule."
         compilation_options = {
             "enabled_precisions": (
                 enabled_precisions
@@ -645,7 +645,7 @@ 
    Source code for torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule"require_full_compilation": require_full_compilation,
             "disable_tf32": disable_tf32,
             "sparse_weights": sparse_weights,
-            "make_refittable": make_refittable,
+            "immutable_weights": immutable_weights,
             "engine_capability": engine_capability,
             "dla_sram_size": dla_sram_size,
             "dla_local_dram_size": dla_local_dram_size,
diff --git a/docs/_modules/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.html b/docs/_modules/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.html
index d3345710f9..9f46b3bdf2 100644
--- a/docs/_modules/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.html
+++ b/docs/_modules/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.dynamo.runtime._PythonTorchTensorRTModule — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.dynamo.runtime._PythonTorchTensorRTModule — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -503,7 +503,7 @@ 
    Source code for torch_tensorrt.dynamo.runtime._PythonTorchTensorRTModule
    *,
         name: str = "",
         settings: CompilationSettings = CompilationSettings(),
-        weight_name_map: Any = None,
+        weight_name_map: Optional[dict[Any, Any]] = None,
     ):
         """Takes a name, target device, serialized TensorRT engine, and binding names / order and constructs
         a PyTorch ``torch.nn.Module`` around it. Uses TensorRT Python APIs to run the engine
@@ -516,6 +516,7 @@ 
    Source code for torch_tensorrt.dynamo.runtime._PythonTorchTensorRTModule
            Keyword Arguments:
             name (str): Name for module
             settings (torch_tensorrt.dynamo.CompilationSettings): Settings used to compile engine, assumes engine was built with default compilation settings if object not passed
+            weight_name_map (dict): Mapping of engine weight name to state_dict weight name
 
         Example:
 
diff --git a/docs/_modules/torch_tensorrt/dynamo/runtime/_TorchTensorRTModule.html b/docs/_modules/torch_tensorrt/dynamo/runtime/_TorchTensorRTModule.html
index b74aebca01..10ab7032a0 100644
--- a/docs/_modules/torch_tensorrt/dynamo/runtime/_TorchTensorRTModule.html
+++ b/docs/_modules/torch_tensorrt/dynamo/runtime/_TorchTensorRTModule.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.dynamo.runtime._TorchTensorRTModule — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.dynamo.runtime._TorchTensorRTModule — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -561,6 +561,7 @@ 
    Source code for torch_tensorrt.dynamo.runtime._TorchTensorRTModule
            Keyword Arguments:
             name (str): Name for module
             settings (torch_tensorrt.dynamo.CompilationSettings): Settings used to compile engine, assumes engine was built with default compilation settings if object not passed
+            weight_name_map (dict): Mapping of engine weight name to state_dict weight name
 
         Example:
 
diff --git a/docs/_modules/torch_tensorrt/fx/fx2trt.html b/docs/_modules/torch_tensorrt/fx/fx2trt.html
index 0989c6c924..c8f70c132d 100644
--- a/docs/_modules/torch_tensorrt/fx/fx2trt.html
+++ b/docs/_modules/torch_tensorrt/fx/fx2trt.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.fx.fx2trt — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.fx.fx2trt — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/_modules/torch_tensorrt/fx/input_tensor_spec.html b/docs/_modules/torch_tensorrt/fx/input_tensor_spec.html
index 258382426e..c68048c676 100644
--- a/docs/_modules/torch_tensorrt/fx/input_tensor_spec.html
+++ b/docs/_modules/torch_tensorrt/fx/input_tensor_spec.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.fx.input_tensor_spec — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.fx.input_tensor_spec — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/_modules/torch_tensorrt/fx/lower.html b/docs/_modules/torch_tensorrt/fx/lower.html
index 001b23e740..e843da421b 100644
--- a/docs/_modules/torch_tensorrt/fx/lower.html
+++ b/docs/_modules/torch_tensorrt/fx/lower.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.fx.lower — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.fx.lower — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/_modules/torch_tensorrt/fx/trt_module.html b/docs/_modules/torch_tensorrt/fx/trt_module.html
index d7db657580..301a2ceaa0 100644
--- a/docs/_modules/torch_tensorrt/fx/trt_module.html
+++ b/docs/_modules/torch_tensorrt/fx/trt_module.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.fx.trt_module — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.fx.trt_module — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/_modules/torch_tensorrt/logging.html b/docs/_modules/torch_tensorrt/logging.html
index 25a3445fc4..8435f2e609 100644
--- a/docs/_modules/torch_tensorrt/logging.html
+++ b/docs/_modules/torch_tensorrt/logging.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.logging — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.logging — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/_modules/torch_tensorrt/runtime/_multi_device_safe_mode.html b/docs/_modules/torch_tensorrt/runtime/_multi_device_safe_mode.html
index 30ff590cd3..459181ac1b 100644
--- a/docs/_modules/torch_tensorrt/runtime/_multi_device_safe_mode.html
+++ b/docs/_modules/torch_tensorrt/runtime/_multi_device_safe_mode.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.runtime._multi_device_safe_mode — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.runtime._multi_device_safe_mode — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/_modules/torch_tensorrt/ts/_compile_spec.html b/docs/_modules/torch_tensorrt/ts/_compile_spec.html
index 1116b7efac..d0d138980f 100644
--- a/docs/_modules/torch_tensorrt/ts/_compile_spec.html
+++ b/docs/_modules/torch_tensorrt/ts/_compile_spec.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.ts._compile_spec — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.ts._compile_spec — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/_modules/torch_tensorrt/ts/_compiler.html b/docs/_modules/torch_tensorrt/ts/_compiler.html
index 3531a2d8d6..7254051358 100644
--- a/docs/_modules/torch_tensorrt/ts/_compiler.html
+++ b/docs/_modules/torch_tensorrt/ts/_compiler.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.ts._compiler — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.ts._compiler — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/_modules/torch_tensorrt/ts/ptq.html b/docs/_modules/torch_tensorrt/ts/ptq.html
index d47cc49aa7..77c8192982 100644
--- a/docs/_modules/torch_tensorrt/ts/ptq.html
+++ b/docs/_modules/torch_tensorrt/ts/ptq.html
@@ -9,7 +9,7 @@
   
   
   
-  torch_tensorrt.ts.ptq — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.ts.ptq — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/_sources/tutorials/_rendered_examples/dynamo/engine_caching_bert_example.rst.txt b/docs/_sources/tutorials/_rendered_examples/dynamo/engine_caching_bert_example.rst.txt
index 5b7760d73f..cc84e2b968 100644
--- a/docs/_sources/tutorials/_rendered_examples/dynamo/engine_caching_bert_example.rst.txt
+++ b/docs/_sources/tutorials/_rendered_examples/dynamo/engine_caching_bert_example.rst.txt
@@ -74,7 +74,7 @@ Small caching example on BERT.
                 "truncate_double": True,
                 "debug": False,
                 "min_block_size": 1,
-                "make_refittable": True,
+                "immutable_weights": False,
                 "cache_built_engines": cache_built_engines,
                 "reuse_cached_engines": reuse_cached_engines,
                 "engine_cache_dir": "/tmp/torch_trt_bert_engine_cache",
diff --git a/docs/_sources/tutorials/_rendered_examples/dynamo/engine_caching_example.rst.txt b/docs/_sources/tutorials/_rendered_examples/dynamo/engine_caching_example.rst.txt
index b81b2c7f1a..a21b53f623 100644
--- a/docs/_sources/tutorials/_rendered_examples/dynamo/engine_caching_example.rst.txt
+++ b/docs/_sources/tutorials/_rendered_examples/dynamo/engine_caching_example.rst.txt
@@ -87,7 +87,7 @@ engines are saved to disk tied to a hash of their corresponding PyTorch subgraph
 in a subsequent compilation, either as part of this session or a new session, the cache will
 pull the built engine and **refit** the weights which can reduce compilation times by orders of magnitude.
 As such, in order to insert a new engine into the cache (i.e. ``cache_built_engines=True``),
-the engine must be refittable (``make_refittable=True``). See :ref:`refit_engine_example` for more details.
+the engine must be refittable (``immutable_weights=False``). See :ref:`refit_engine_example` for more details.
 
 .. GENERATED FROM PYTHON SOURCE LINES 67-118
 
@@ -126,7 +126,7 @@ the engine must be refittable (``make_refittable=True``). See :ref:`refit_engine
                     "enabled_precisions": enabled_precisions,
                     "debug": debug,
                     "min_block_size": min_block_size,
-                    "make_refittable": True,
+                    "immutable_weights": False,
                     "cache_built_engines": cache_built_engines,
                     "reuse_cached_engines": reuse_cached_engines,
                 },
@@ -193,7 +193,7 @@ previously built engines and refit the weights.
                 enabled_precisions=enabled_precisions,
                 debug=debug,
                 min_block_size=min_block_size,
-                make_refittable=True,
+                immutable_weights=False,
                 cache_built_engines=cache_built_engines,
                 reuse_cached_engines=reuse_cached_engines,
                 engine_cache_size=1 << 30,  # 1GB
@@ -311,7 +311,7 @@ Below is an example of a custom engine cache implementation that implents a ``RA
                     "enabled_precisions": enabled_precisions,
                     "debug": debug,
                     "min_block_size": min_block_size,
-                    "make_refittable": True,
+                    "immutable_weights": False,
                     "cache_built_engines": cache_built_engines,
                     "reuse_cached_engines": reuse_cached_engines,
                     "custom_engine_cache": engine_cache,
diff --git a/docs/_sources/tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.rst.txt b/docs/_sources/tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.rst.txt
index cd15592a25..70ec515462 100644
--- a/docs/_sources/tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.rst.txt
+++ b/docs/_sources/tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.rst.txt
@@ -61,7 +61,7 @@ Initialize the Mutable Torch TensorRT Module with settings.
     settings = {
         "use_python": False,
         "enabled_precisions": {torch.float32},
-        "make_refittable": True,
+        "immutable_weights": False,
     }
 
     model = models.resnet18(pretrained=True).eval().to("cuda")
@@ -132,7 +132,7 @@ Stable Diffusion with Huggingface
             "use_python_runtime": True,
             "enabled_precisions": {torch.float16},
             "debug": True,
-            "make_refittable": True,
+            "immutable_weights": False,
         }
 
         model_id = "runwayml/stable-diffusion-v1-5"
diff --git a/docs/_sources/tutorials/_rendered_examples/dynamo/refit_engine_example.rst.txt b/docs/_sources/tutorials/_rendered_examples/dynamo/refit_engine_example.rst.txt
index d371ecc887..c0acbf4cb8 100644
--- a/docs/_sources/tutorials/_rendered_examples/dynamo/refit_engine_example.rst.txt
+++ b/docs/_sources/tutorials/_rendered_examples/dynamo/refit_engine_example.rst.txt
@@ -74,7 +74,7 @@ Make a refittable Compilation Program
 ---------------------------------------
 
 The inital step is to compile a module and save it as with a normal. Note that there is an
-additional parameter `make_refittable` that is set to `True`. This parameter is used to
+additional parameter `immutable_weights` that is set to `False`. This parameter is used to
 indicate that the engine being built should support weight refitting later. Engines built without
 these setttings will not be able to be refit.
 
@@ -101,7 +101,7 @@ In this case we are going to compile a ResNet18 model with randomly initialized
         debug=debug,
         min_block_size=min_block_size,
         torch_executed_ops=torch_executed_ops,
-        make_refittable=True,
+        immutable_weights=False,
         reuse_cached_engines=False,
     )  # Output is a torch.fx.GraphModule
 
diff --git a/docs/_static/documentation_options.js b/docs/_static/documentation_options.js
index 3a895a549f..df87ba5405 100644
--- a/docs/_static/documentation_options.js
+++ b/docs/_static/documentation_options.js
@@ -1,6 +1,6 @@
 var DOCUMENTATION_OPTIONS = {
     URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'),
-    VERSION: 'v2.6.0.dev0+a945aeb',
+    VERSION: 'v2.6.0.dev0+93b5b8f',
     LANGUAGE: 'en',
     COLLAPSE_INDEX: false,
     BUILDER: 'html',
diff --git a/docs/cli/torchtrtc.html b/docs/cli/torchtrtc.html
index 89265e17aa..bc1e867e6e 100644
--- a/docs/cli/torchtrtc.html
+++ b/docs/cli/torchtrtc.html
@@ -10,7 +10,7 @@
 
   
   
-  torchtrtc — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torchtrtc — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/contributors/conversion.html b/docs/contributors/conversion.html
index 2430092138..76a088fc4d 100644
--- a/docs/contributors/conversion.html
+++ b/docs/contributors/conversion.html
@@ -10,7 +10,7 @@
 
   
   
-  Conversion Phase — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Conversion Phase — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/contributors/dynamo_converters.html b/docs/contributors/dynamo_converters.html
index f14b1cd5ad..a9e784ad1f 100644
--- a/docs/contributors/dynamo_converters.html
+++ b/docs/contributors/dynamo_converters.html
@@ -10,7 +10,7 @@
 
   
   
-  Writing Dynamo Converters — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Writing Dynamo Converters — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/contributors/lowering.html b/docs/contributors/lowering.html
index e94e89c522..f9b1b59af1 100644
--- a/docs/contributors/lowering.html
+++ b/docs/contributors/lowering.html
@@ -10,7 +10,7 @@
 
   
   
-  Lowering Phase — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Lowering Phase — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/contributors/partitioning.html b/docs/contributors/partitioning.html
index 0630ddd942..65ed2ac06e 100644
--- a/docs/contributors/partitioning.html
+++ b/docs/contributors/partitioning.html
@@ -10,7 +10,7 @@
 
   
   
-  Partitioning Phase — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Partitioning Phase — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/contributors/phases.html b/docs/contributors/phases.html
index 776fd09aab..61564bbc00 100644
--- a/docs/contributors/phases.html
+++ b/docs/contributors/phases.html
@@ -10,7 +10,7 @@
 
   
   
-  Compiler Phases — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Compiler Phases — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -273,7 +273,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/contributors/runtime.html b/docs/contributors/runtime.html
index 04c05e5c5d..0e20f6b166 100644
--- a/docs/contributors/runtime.html
+++ b/docs/contributors/runtime.html
@@ -10,7 +10,7 @@
 
   
   
-  Runtime Phase — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Runtime Phase — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/contributors/system_overview.html b/docs/contributors/system_overview.html
index 4c93b63465..e18d7daeea 100644
--- a/docs/contributors/system_overview.html
+++ b/docs/contributors/system_overview.html
@@ -10,7 +10,7 @@
 
   
   
-  System Overview — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  System Overview — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/contributors/ts_converters.html b/docs/contributors/ts_converters.html
index 7381ad2c5d..be44cee0e8 100644
--- a/docs/contributors/ts_converters.html
+++ b/docs/contributors/ts_converters.html
@@ -10,7 +10,7 @@
 
   
   
-  Writing TorchScript Converters — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Writing TorchScript Converters — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/contributors/useful_links.html b/docs/contributors/useful_links.html
index b4a533f47a..f5bfe3f8f1 100644
--- a/docs/contributors/useful_links.html
+++ b/docs/contributors/useful_links.html
@@ -10,7 +10,7 @@
 
   
   
-  Useful Links for Torch-TensorRT Development — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Useful Links for Torch-TensorRT Development — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/contributors/writing_dynamo_aten_lowering_passes.html b/docs/contributors/writing_dynamo_aten_lowering_passes.html
index 8d5b5b1cb1..63d8101ebe 100644
--- a/docs/contributors/writing_dynamo_aten_lowering_passes.html
+++ b/docs/contributors/writing_dynamo_aten_lowering_passes.html
@@ -10,7 +10,7 @@
 
   
   
-  Writing Dynamo ATen Lowering Passes — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Writing Dynamo ATen Lowering Passes — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/dynamo/dynamo_export.html b/docs/dynamo/dynamo_export.html
index 1dcb8245e9..7e8a282b8e 100644
--- a/docs/dynamo/dynamo_export.html
+++ b/docs/dynamo/dynamo_export.html
@@ -10,7 +10,7 @@
 
   
   
-  Compiling Exported Programs with Torch-TensorRT — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Compiling Exported Programs with Torch-TensorRT — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/dynamo/torch_compile.html b/docs/dynamo/torch_compile.html
index c7ac92b318..76e533b616 100644
--- a/docs/dynamo/torch_compile.html
+++ b/docs/dynamo/torch_compile.html
@@ -10,7 +10,7 @@
 
   
   
-  TensorRT Backend for torch.compile — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  TensorRT Backend for torch.compile — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -488,7 +488,7 @@ 
    Key Features
    
 
    
 
    
-class torch_tensorrt.dynamo.CompilationSettings(enabled_precisions: ~typing.Set[~torch_tensorrt._enums.dtype] = <factory>, debug: bool = False, workspace_size: int = 0, min_block_size: int = 5, torch_executed_ops: ~typing.Collection[~typing.Union[~typing.Callable[[...], ~typing.Any], str]] = <factory>, pass_through_build_failures: bool = False, max_aux_streams: ~typing.Optional[int] = None, version_compatible: bool = False, optimization_level: ~typing.Optional[int] = None, use_python_runtime: ~typing.Optional[bool] = False, truncate_double: bool = False, use_fast_partitioner: bool = True, enable_experimental_decompositions: bool = False, device: ~torch_tensorrt._Device.Device = <factory>, require_full_compilation: bool = False, disable_tf32: bool = False, assume_dynamic_shape_support: bool = False, sparse_weights: bool = False, make_refittable: bool = False, engine_capability: ~torch_tensorrt._enums.EngineCapability = <factory>, num_avg_timing_iters: int = 1, dla_sram_size: int = 1048576, dla_local_dram_size: int = 1073741824, dla_global_dram_size: int = 536870912, dryrun: ~typing.Union[bool, str] = False, hardware_compatible: bool = False, timing_cache_path: str = '/tmp/torch_tensorrt_engine_cache/timing_cache.bin', lazy_engine_init: bool = False, cache_built_engines: bool = False, reuse_cached_engines: bool = False, use_explicit_typing: bool = False, use_fp32_acc: bool = False, enable_weight_streaming: bool = False, enable_cross_compile_for_windows: bool = False)[source]
    
+class torch_tensorrt.dynamo.CompilationSettings(enabled_precisions: ~typing.Set[~torch_tensorrt._enums.dtype] = <factory>, debug: bool = False, workspace_size: int = 0, min_block_size: int = 5, torch_executed_ops: ~typing.Collection[~typing.Union[~typing.Callable[[...], ~typing.Any], str]] = <factory>, pass_through_build_failures: bool = False, max_aux_streams: ~typing.Optional[int] = None, version_compatible: bool = False, optimization_level: ~typing.Optional[int] = None, use_python_runtime: ~typing.Optional[bool] = False, truncate_double: bool = False, use_fast_partitioner: bool = True, enable_experimental_decompositions: bool = False, device: ~torch_tensorrt._Device.Device = <factory>, require_full_compilation: bool = False, disable_tf32: bool = False, assume_dynamic_shape_support: bool = False, sparse_weights: bool = False, engine_capability: ~torch_tensorrt._enums.EngineCapability = <factory>, num_avg_timing_iters: int = 1, dla_sram_size: int = 1048576, dla_local_dram_size: int = 1073741824, dla_global_dram_size: int = 536870912, dryrun: ~typing.Union[bool, str] = False, hardware_compatible: bool = False, timing_cache_path: str = '/tmp/torch_tensorrt_engine_cache/timing_cache.bin', lazy_engine_init: bool = False, cache_built_engines: bool = False, reuse_cached_engines: bool = False, use_explicit_typing: bool = False, use_fp32_acc: bool = False, refit_identical_engine_weights: bool = False, strip_engine_weights: bool = False, immutable_weights: bool = True, enable_weight_streaming: bool = False, enable_cross_compile_for_windows: bool = False)[source]
 
    Compilation settings for Torch-TensorRT Dynamo Paths
    
 
    
 
    Parameters
    
@@ -516,7 +516,6 @@ 
    Customizable Settings
    assume_dynamic_shape_support (bool) – Setting this to true enables the converters work for both dynamic and static shapes. Default: False
    
 
  • disable_tf32 (bool) – Whether to disable TF32 computation for TRT layers
    • 
 
  • sparse_weights (bool) – Whether to allow the builder to use sparse weights
    • 
-
  • refit (bool) – Whether to build a refittable engine
    • 
 
  • engine_capability (trt.EngineCapability) – Restrict kernel selection to safe gpu kernels or safe dla kernels
    • 
 
  • num_avg_timing_iters (python:int) – Number of averaging timing iterations used to select kernels
    • 
 
  • dla_sram_size (python:int) – Fast software managed RAM used by DLA to communicate within a layer.
    • 
@@ -531,6 +530,9 @@ 
    Customizable Settings
    reuse_cached_engines (bool) – Whether to load the compiled TRT engines from storage
    
 
  • use_strong_typing (bool) – This flag enables strong typing in TensorRT compilation which respects the precisions set in the Pytorch model. This is useful when users have mixed precision graphs.
    • 
 
  • use_fp32_acc (bool) – This option inserts cast to FP32 nodes around matmul layers and TensorRT ensures the accumulation of matmul happens in FP32. Use this only when FP16 precision is configured in enabled_precisions.
    • 
+
  • refit_identical_engine_weights (bool) – Whether to refit the engine with identical weights
    • 
+
  • strip_engine_weights (bool) – Whether to strip the engine weights
    • 
+
  • immutable_weights (bool) – Build non-refittable engines. This is useful for some layers that are not refittable. If this argument is set to true, strip_engine_weights and refit_identical_engine_weights will be ignored
    • 
 
  • enable_weight_streaming (bool) – Enable weight streaming.
    • 
 
  • enable_cross_compile_for_windows (bool) – By default this is False means TensorRT engines can only be executed on the same platform where they were built.
 True will enable cross-platform compatibility which allows the engine to be built on Linux and run on Windows
    • 
diff --git a/docs/fx/getting_started_with_fx_path.html b/docs/fx/getting_started_with_fx_path.html
index 98d255ea54..5b5f084c9c 100644
--- a/docs/fx/getting_started_with_fx_path.html
+++ b/docs/fx/getting_started_with_fx_path.html
@@ -10,7 +10,7 @@
 
   
   
-  Torch-TensorRT (FX Frontend) User Guide — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Torch-TensorRT (FX Frontend) User Guide — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/genindex.html b/docs/genindex.html
index 1abce9d54f..ab311c1c24 100644
--- a/docs/genindex.html
+++ b/docs/genindex.html
@@ -9,7 +9,7 @@
   
   
   
-  Index — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Index — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/getting_started/installation.html b/docs/getting_started/installation.html
index 60da70d4b3..75759416bf 100644
--- a/docs/getting_started/installation.html
+++ b/docs/getting_started/installation.html
@@ -10,7 +10,7 @@
 
   
   
-  Installation — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Installation — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/getting_started/jetpack.html b/docs/getting_started/jetpack.html
index 214b086ad7..7e4671c5e2 100644
--- a/docs/getting_started/jetpack.html
+++ b/docs/getting_started/jetpack.html
@@ -10,7 +10,7 @@
 
   
   
-  Overview — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Overview — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/getting_started/quick_start.html b/docs/getting_started/quick_start.html
index c8ccf89629..14e857353b 100644
--- a/docs/getting_started/quick_start.html
+++ b/docs/getting_started/quick_start.html
@@ -10,7 +10,7 @@
 
   
   
-  Quick Start — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Quick Start — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/index.html b/docs/index.html
index 51dfc4cd13..37c2ca487f 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -10,7 +10,7 @@
 
   
   
-  Torch-TensorRT — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Torch-TensorRT — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -274,7 +274,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/indices/supported_ops.html b/docs/indices/supported_ops.html
index 232a4cb965..e89167c230 100644
--- a/docs/indices/supported_ops.html
+++ b/docs/indices/supported_ops.html
@@ -10,7 +10,7 @@
 
   
   
-  Operators Supported — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Operators Supported — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -274,7 +274,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/objects.inv b/docs/objects.inv
index 456ee96582ea987f53d1c30ef54a0085ed4c8c8c..59a973f0968ed75361d78e0c7054179d5f896c4a 100644
GIT binary patch
delta 20
bcmX@n$aJESX@VcSrE!vJl119a(BcLFPrC
   
-  Python Module Index — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Python Module Index — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/py_api/dynamo.html b/docs/py_api/dynamo.html
index 7f6ecbfdf0..add4e9afc1 100644
--- a/docs/py_api/dynamo.html
+++ b/docs/py_api/dynamo.html
@@ -10,7 +10,7 @@
 
   
   
-  torch_tensorrt.dynamo — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.dynamo — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -475,7 +475,7 @@
 
    Functions
    
 
    
 
    
-torch_tensorrt.dynamo.compile(exported_program: ExportedProgram, inputs: Optional[Sequence[Sequence[Any]]] = None, *, arg_inputs: Optional[Sequence[Sequence[Any]]] = None, kwarg_inputs: Optional[dict[Any, Any]] = None, device: Optional[Union[Device, device, str]] = None, disable_tf32: bool = False, assume_dynamic_shape_support: bool = False, sparse_weights: bool = False, enabled_precisions: Union[Set[Union[dtype, dtype]], Tuple[Union[dtype, dtype]]] = {dtype.f32}, engine_capability: EngineCapability = EngineCapability.STANDARD, make_refittable: bool = False, debug: bool = False, num_avg_timing_iters: int = 1, workspace_size: int = 0, dla_sram_size: int = 1048576, dla_local_dram_size: int = 1073741824, dla_global_dram_size: int = 536870912, truncate_double: bool = False, require_full_compilation: bool = False, min_block_size: int = 5, torch_executed_ops: Optional[Collection[Union[Callable[[...], Any], str]]] = None, torch_executed_modules: Optional[List[str]] = None, pass_through_build_failures: bool = False, max_aux_streams: Optional[int] = None, version_compatible: bool = False, optimization_level: Optional[int] = None, use_python_runtime: bool = False, use_fast_partitioner: bool = True, enable_experimental_decompositions: bool = False, dryrun: bool = False, hardware_compatible: bool = False, timing_cache_path: str = '/tmp/torch_tensorrt_engine_cache/timing_cache.bin', lazy_engine_init: bool = False, cache_built_engines: bool = False, reuse_cached_engines: bool = False, engine_cache_dir: str = '/tmp/torch_tensorrt_engine_cache', engine_cache_size: int = 1073741824, custom_engine_cache: Optional[BaseEngineCache] = None, use_explicit_typing: bool = False, use_fp32_acc: bool = False, enable_weight_streaming: bool = False, **kwargs: Any) → GraphModule[source]
    
+torch_tensorrt.dynamo.compile(exported_program: ExportedProgram, inputs: Optional[Sequence[Sequence[Any]]] = None, *, arg_inputs: Optional[Sequence[Sequence[Any]]] = None, kwarg_inputs: Optional[dict[Any, Any]] = None, device: Optional[Union[Device, device, str]] = None, disable_tf32: bool = False, assume_dynamic_shape_support: bool = False, sparse_weights: bool = False, enabled_precisions: Union[Set[Union[dtype, dtype]], Tuple[Union[dtype, dtype]]] = {dtype.f32}, engine_capability: EngineCapability = EngineCapability.STANDARD, debug: bool = False, num_avg_timing_iters: int = 1, workspace_size: int = 0, dla_sram_size: int = 1048576, dla_local_dram_size: int = 1073741824, dla_global_dram_size: int = 536870912, truncate_double: bool = False, require_full_compilation: bool = False, min_block_size: int = 5, torch_executed_ops: Optional[Collection[Union[Callable[[...], Any], str]]] = None, torch_executed_modules: Optional[List[str]] = None, pass_through_build_failures: bool = False, max_aux_streams: Optional[int] = None, version_compatible: bool = False, optimization_level: Optional[int] = None, use_python_runtime: bool = False, use_fast_partitioner: bool = True, enable_experimental_decompositions: bool = False, dryrun: bool = False, hardware_compatible: bool = False, timing_cache_path: str = '/tmp/torch_tensorrt_engine_cache/timing_cache.bin', lazy_engine_init: bool = False, cache_built_engines: bool = False, reuse_cached_engines: bool = False, engine_cache_dir: str = '/tmp/torch_tensorrt_engine_cache', engine_cache_size: int = 5368709120, custom_engine_cache: Optional[BaseEngineCache] = None, use_explicit_typing: bool = False, use_fp32_acc: bool = False, refit_identical_engine_weights: bool = False, strip_engine_weights: bool = False, immutable_weights: bool = True, enable_weight_streaming: bool = False, **kwargs: Any) → GraphModule[source]
 
    Compile an ExportedProgram module for NVIDIA GPUs using TensorRT
    
 
    Takes a existing TorchScript module and a set of settings to configure the compiler
 and will convert methods to JIT Graphs which call equivalent TensorRT engines
    
@@ -518,7 +518,6 @@ 
    FunctionsEngineCapability) – Restrict kernel selection to safe gpu kernels or safe dla kernels
    
 
  • num_avg_timing_iters (python:int) – Number of averaging timing iterations used to select kernels
    • 
@@ -550,6 +549,9 @@ 
    Functions
    
 
    
 
    
-class torch_tensorrt.dynamo.CompilationSettings(enabled_precisions: ~typing.Set[~torch_tensorrt._enums.dtype] = <factory>, debug: bool = False, workspace_size: int = 0, min_block_size: int = 5, torch_executed_ops: ~typing.Collection[~typing.Union[~typing.Callable[[...], ~typing.Any], str]] = <factory>, pass_through_build_failures: bool = False, max_aux_streams: ~typing.Optional[int] = None, version_compatible: bool = False, optimization_level: ~typing.Optional[int] = None, use_python_runtime: ~typing.Optional[bool] = False, truncate_double: bool = False, use_fast_partitioner: bool = True, enable_experimental_decompositions: bool = False, device: ~torch_tensorrt._Device.Device = <factory>, require_full_compilation: bool = False, disable_tf32: bool = False, assume_dynamic_shape_support: bool = False, sparse_weights: bool = False, make_refittable: bool = False, engine_capability: ~torch_tensorrt._enums.EngineCapability = <factory>, num_avg_timing_iters: int = 1, dla_sram_size: int = 1048576, dla_local_dram_size: int = 1073741824, dla_global_dram_size: int = 536870912, dryrun: ~typing.Union[bool, str] = False, hardware_compatible: bool = False, timing_cache_path: str = '/tmp/torch_tensorrt_engine_cache/timing_cache.bin', lazy_engine_init: bool = False, cache_built_engines: bool = False, reuse_cached_engines: bool = False, use_explicit_typing: bool = False, use_fp32_acc: bool = False, enable_weight_streaming: bool = False, enable_cross_compile_for_windows: bool = False)[source]
    
+class torch_tensorrt.dynamo.CompilationSettings(enabled_precisions: ~typing.Set[~torch_tensorrt._enums.dtype] = <factory>, debug: bool = False, workspace_size: int = 0, min_block_size: int = 5, torch_executed_ops: ~typing.Collection[~typing.Union[~typing.Callable[[...], ~typing.Any], str]] = <factory>, pass_through_build_failures: bool = False, max_aux_streams: ~typing.Optional[int] = None, version_compatible: bool = False, optimization_level: ~typing.Optional[int] = None, use_python_runtime: ~typing.Optional[bool] = False, truncate_double: bool = False, use_fast_partitioner: bool = True, enable_experimental_decompositions: bool = False, device: ~torch_tensorrt._Device.Device = <factory>, require_full_compilation: bool = False, disable_tf32: bool = False, assume_dynamic_shape_support: bool = False, sparse_weights: bool = False, engine_capability: ~torch_tensorrt._enums.EngineCapability = <factory>, num_avg_timing_iters: int = 1, dla_sram_size: int = 1048576, dla_local_dram_size: int = 1073741824, dla_global_dram_size: int = 536870912, dryrun: ~typing.Union[bool, str] = False, hardware_compatible: bool = False, timing_cache_path: str = '/tmp/torch_tensorrt_engine_cache/timing_cache.bin', lazy_engine_init: bool = False, cache_built_engines: bool = False, reuse_cached_engines: bool = False, use_explicit_typing: bool = False, use_fp32_acc: bool = False, refit_identical_engine_weights: bool = False, strip_engine_weights: bool = False, immutable_weights: bool = True, enable_weight_streaming: bool = False, enable_cross_compile_for_windows: bool = False)[source]
 
    Compilation settings for Torch-TensorRT Dynamo Paths
    
 
    
 
    Parameters
    
@@ -685,7 +687,6 @@ 
    Classes
   
-  torch_tensorrt.fx — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.fx — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/py_api/logging.html b/docs/py_api/logging.html
index 2381d7eb43..ec08cba924 100644
--- a/docs/py_api/logging.html
+++ b/docs/py_api/logging.html
@@ -10,7 +10,7 @@
 
   
   
-  torch_tensorrt.logging — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.logging — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/py_api/ptq.html b/docs/py_api/ptq.html
index 11993a323d..a6d05070a4 100644
--- a/docs/py_api/ptq.html
+++ b/docs/py_api/ptq.html
@@ -10,7 +10,7 @@
 
   
   
-  torch_tensorrt.ts.ptq — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.ts.ptq — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/py_api/runtime.html b/docs/py_api/runtime.html
index 8c3307726e..4683740b9b 100644
--- a/docs/py_api/runtime.html
+++ b/docs/py_api/runtime.html
@@ -10,7 +10,7 @@
 
   
   
-  torch_tensorrt.runtime — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.runtime — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -577,13 +577,13 @@ 
    Classes
 
    
-class torch_tensorrt.runtime.PythonTorchTensorRTModule(serialized_engine: ~typing.Optional[bytes] = None, input_binding_names: ~typing.Optional[~typing.List[str]] = None, output_binding_names: ~typing.Optional[~typing.List[str]] = None, *, name: str = '', settings: ~torch_tensorrt.dynamo._settings.CompilationSettings = CompilationSettings(enabled_precisions={<dtype.f32: 7>}, debug=False, workspace_size=0, min_block_size=5, torch_executed_ops=set(), pass_through_build_failures=False, max_aux_streams=None, version_compatible=False, optimization_level=None, use_python_runtime=False, truncate_double=False, use_fast_partitioner=True, enable_experimental_decompositions=False, device=Device(type=DeviceType.GPU, gpu_id=0), require_full_compilation=False, disable_tf32=False, assume_dynamic_shape_support=False, sparse_weights=False, make_refittable=False, engine_capability=<EngineCapability.STANDARD: 1>, num_avg_timing_iters=1, dla_sram_size=1048576, dla_local_dram_size=1073741824, dla_global_dram_size=536870912, dryrun=False, hardware_compatible=False, timing_cache_path='/tmp/torch_tensorrt_engine_cache/timing_cache.bin', lazy_engine_init=False, cache_built_engines=False, reuse_cached_engines=False, use_explicit_typing=False, use_fp32_acc=False, enable_weight_streaming=False, enable_cross_compile_for_windows=False), weight_name_map: ~typing.Any = None)[source]
    
+class torch_tensorrt.runtime.PythonTorchTensorRTModule(serialized_engine: ~typing.Optional[bytes] = None, input_binding_names: ~typing.Optional[~typing.List[str]] = None, output_binding_names: ~typing.Optional[~typing.List[str]] = None, *, name: str = '', settings: ~torch_tensorrt.dynamo._settings.CompilationSettings = CompilationSettings(enabled_precisions={<dtype.f32: 7>}, debug=False, workspace_size=0, min_block_size=5, torch_executed_ops=set(), pass_through_build_failures=False, max_aux_streams=None, version_compatible=False, optimization_level=None, use_python_runtime=False, truncate_double=False, use_fast_partitioner=True, enable_experimental_decompositions=False, device=Device(type=DeviceType.GPU, gpu_id=0), require_full_compilation=False, disable_tf32=False, assume_dynamic_shape_support=False, sparse_weights=False, engine_capability=<EngineCapability.STANDARD: 1>, num_avg_timing_iters=1, dla_sram_size=1048576, dla_local_dram_size=1073741824, dla_global_dram_size=536870912, dryrun=False, hardware_compatible=False, timing_cache_path='/tmp/torch_tensorrt_engine_cache/timing_cache.bin', lazy_engine_init=False, cache_built_engines=False, reuse_cached_engines=False, use_explicit_typing=False, use_fp32_acc=False, refit_identical_engine_weights=False, strip_engine_weights=False, immutable_weights=True, enable_weight_streaming=False, enable_cross_compile_for_windows=False), weight_name_map: ~typing.Optional[dict[typing.Any, typing.Any]] = None)[source]
 
    PythonTorchTensorRTModule is a PyTorch module which encompasses an arbitrary TensorRT Engine.
    
 
    This module is backed by the Torch-TensorRT runtime and is only compatible with
 FX / Dynamo / Python deployments. This module cannot be serialized to torchscript via torch.jit.trace for C++ deployment.
    
 
    
 
    
-__init__(serialized_engine: ~typing.Optional[bytes] = None, input_binding_names: ~typing.Optional[~typing.List[str]] = None, output_binding_names: ~typing.Optional[~typing.List[str]] = None, *, name: str = '', settings: ~torch_tensorrt.dynamo._settings.CompilationSettings = CompilationSettings(enabled_precisions={<dtype.f32: 7>}, debug=False, workspace_size=0, min_block_size=5, torch_executed_ops=set(), pass_through_build_failures=False, max_aux_streams=None, version_compatible=False, optimization_level=None, use_python_runtime=False, truncate_double=False, use_fast_partitioner=True, enable_experimental_decompositions=False, device=Device(type=DeviceType.GPU, gpu_id=0), require_full_compilation=False, disable_tf32=False, assume_dynamic_shape_support=False, sparse_weights=False, make_refittable=False, engine_capability=<EngineCapability.STANDARD: 1>, num_avg_timing_iters=1, dla_sram_size=1048576, dla_local_dram_size=1073741824, dla_global_dram_size=536870912, dryrun=False, hardware_compatible=False, timing_cache_path='/tmp/torch_tensorrt_engine_cache/timing_cache.bin', lazy_engine_init=False, cache_built_engines=False, reuse_cached_engines=False, use_explicit_typing=False, use_fp32_acc=False, enable_weight_streaming=False, enable_cross_compile_for_windows=False), weight_name_map: ~typing.Any = None)[source]
    
+__init__(serialized_engine: ~typing.Optional[bytes] = None, input_binding_names: ~typing.Optional[~typing.List[str]] = None, output_binding_names: ~typing.Optional[~typing.List[str]] = None, *, name: str = '', settings: ~torch_tensorrt.dynamo._settings.CompilationSettings = CompilationSettings(enabled_precisions={<dtype.f32: 7>}, debug=False, workspace_size=0, min_block_size=5, torch_executed_ops=set(), pass_through_build_failures=False, max_aux_streams=None, version_compatible=False, optimization_level=None, use_python_runtime=False, truncate_double=False, use_fast_partitioner=True, enable_experimental_decompositions=False, device=Device(type=DeviceType.GPU, gpu_id=0), require_full_compilation=False, disable_tf32=False, assume_dynamic_shape_support=False, sparse_weights=False, engine_capability=<EngineCapability.STANDARD: 1>, num_avg_timing_iters=1, dla_sram_size=1048576, dla_local_dram_size=1073741824, dla_global_dram_size=536870912, dryrun=False, hardware_compatible=False, timing_cache_path='/tmp/torch_tensorrt_engine_cache/timing_cache.bin', lazy_engine_init=False, cache_built_engines=False, reuse_cached_engines=False, use_explicit_typing=False, use_fp32_acc=False, refit_identical_engine_weights=False, strip_engine_weights=False, immutable_weights=True, enable_weight_streaming=False, enable_cross_compile_for_windows=False), weight_name_map: ~typing.Optional[dict[typing.Any, typing.Any]] = None)[source]
 
    Takes a name, target device, serialized TensorRT engine, and binding names / order and constructs
 a PyTorch torch.nn.Module around it. Uses TensorRT Python APIs to run the engine
    
 
    
@@ -598,6 +598,7 @@ 
    Classes
 
    
 
    
diff --git a/docs/py_api/torch_tensorrt.html b/docs/py_api/torch_tensorrt.html
index d3511080b1..f56daa8a5a 100644
--- a/docs/py_api/torch_tensorrt.html
+++ b/docs/py_api/torch_tensorrt.html
@@ -10,7 +10,7 @@
 
   
   
-  torch_tensorrt — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -601,7 +601,7 @@ 
    Functions
    
 
    
 
    
-class torch_tensorrt.MutableTorchTensorRTModule(pytorch_model: Module, *, device: Optional[Union[Device, device, str]] = None, disable_tf32: bool = False, assume_dynamic_shape_support: bool = False, sparse_weights: bool = False, enabled_precisions: Set[Union[dtype, dtype]] = {dtype.f32}, engine_capability: EngineCapability = EngineCapability.STANDARD, make_refittable: bool = False, debug: bool = False, num_avg_timing_iters: int = 1, workspace_size: int = 0, dla_sram_size: int = 1048576, dla_local_dram_size: int = 1073741824, dla_global_dram_size: int = 536870912, truncate_double: bool = False, require_full_compilation: bool = False, min_block_size: int = 5, torch_executed_ops: Optional[Collection[Union[Callable[[...], Any], str]]] = None, torch_executed_modules: Optional[List[str]] = None, pass_through_build_failures: bool = False, max_aux_streams: Optional[int] = None, version_compatible: bool = False, optimization_level: Optional[int] = None, use_python_runtime: bool = False, use_fast_partitioner: bool = True, enable_experimental_decompositions: bool = False, dryrun: bool = False, hardware_compatible: bool = False, timing_cache_path: str = '/tmp/torch_tensorrt_engine_cache/timing_cache.bin', **kwargs: Any)[source]
    
+class torch_tensorrt.MutableTorchTensorRTModule(pytorch_model: Module, *, device: Optional[Union[Device, device, str]] = None, disable_tf32: bool = False, assume_dynamic_shape_support: bool = False, sparse_weights: bool = False, enabled_precisions: Set[Union[dtype, dtype]] = {dtype.f32}, engine_capability: EngineCapability = EngineCapability.STANDARD, immutable_weights: bool = True, debug: bool = False, num_avg_timing_iters: int = 1, workspace_size: int = 0, dla_sram_size: int = 1048576, dla_local_dram_size: int = 1073741824, dla_global_dram_size: int = 536870912, truncate_double: bool = False, require_full_compilation: bool = False, min_block_size: int = 5, torch_executed_ops: Optional[Collection[Union[Callable[[...], Any], str]]] = None, torch_executed_modules: Optional[List[str]] = None, pass_through_build_failures: bool = False, max_aux_streams: Optional[int] = None, version_compatible: bool = False, optimization_level: Optional[int] = None, use_python_runtime: bool = False, use_fast_partitioner: bool = True, enable_experimental_decompositions: bool = False, dryrun: bool = False, hardware_compatible: bool = False, timing_cache_path: str = '/tmp/torch_tensorrt_engine_cache/timing_cache.bin', **kwargs: Any)[source]
 
    Initialize a MutableTorchTensorRTModule to seamlessly manipulate it like a regular PyTorch module.
 All TensorRT compilation and refitting processes are handled automatically as you work with the module.
 Any changes to its attributes or loading a different state_dict will trigger refitting or recompilation,
@@ -611,7 +611,7 @@ 
    Classes
 
    
-__init__(pytorch_model: Module, *, device: Optional[Union[Device, device, str]] = None, disable_tf32: bool = False, assume_dynamic_shape_support: bool = False, sparse_weights: bool = False, enabled_precisions: Set[Union[dtype, dtype]] = {dtype.f32}, engine_capability: EngineCapability = EngineCapability.STANDARD, make_refittable: bool = False, debug: bool = False, num_avg_timing_iters: int = 1, workspace_size: int = 0, dla_sram_size: int = 1048576, dla_local_dram_size: int = 1073741824, dla_global_dram_size: int = 536870912, truncate_double: bool = False, require_full_compilation: bool = False, min_block_size: int = 5, torch_executed_ops: Optional[Collection[Union[Callable[[...], Any], str]]] = None, torch_executed_modules: Optional[List[str]] = None, pass_through_build_failures: bool = False, max_aux_streams: Optional[int] = None, version_compatible: bool = False, optimization_level: Optional[int] = None, use_python_runtime: bool = False, use_fast_partitioner: bool = True, enable_experimental_decompositions: bool = False, dryrun: bool = False, hardware_compatible: bool = False, timing_cache_path: str = '/tmp/torch_tensorrt_engine_cache/timing_cache.bin', **kwargs: Any) → None[source]
    
+__init__(pytorch_model: Module, *, device: Optional[Union[Device, device, str]] = None, disable_tf32: bool = False, assume_dynamic_shape_support: bool = False, sparse_weights: bool = False, enabled_precisions: Set[Union[dtype, dtype]] = {dtype.f32}, engine_capability: EngineCapability = EngineCapability.STANDARD, immutable_weights: bool = True, debug: bool = False, num_avg_timing_iters: int = 1, workspace_size: int = 0, dla_sram_size: int = 1048576, dla_local_dram_size: int = 1073741824, dla_global_dram_size: int = 536870912, truncate_double: bool = False, require_full_compilation: bool = False, min_block_size: int = 5, torch_executed_ops: Optional[Collection[Union[Callable[[...], Any], str]]] = None, torch_executed_modules: Optional[List[str]] = None, pass_through_build_failures: bool = False, max_aux_streams: Optional[int] = None, version_compatible: bool = False, optimization_level: Optional[int] = None, use_python_runtime: bool = False, use_fast_partitioner: bool = True, enable_experimental_decompositions: bool = False, dryrun: bool = False, hardware_compatible: bool = False, timing_cache_path: str = '/tmp/torch_tensorrt_engine_cache/timing_cache.bin', **kwargs: Any) → None[source]
 
    
 
    Parameters
    
 
    pytorch_model (torch.nn.module) – Source module that needs to be accelerated
    
@@ -627,7 +627,7 @@ 
    ClassesEngineCapability) – Restrict kernel selection to safe gpu kernels or safe dla kernels
    
 
  • num_avg_timing_iters (python:int) – Number of averaging timing iterations used to select kernels
    • 
diff --git a/docs/py_api/ts.html b/docs/py_api/ts.html
index 0dfed3f6fd..88e9f9e315 100644
--- a/docs/py_api/ts.html
+++ b/docs/py_api/ts.html
@@ -10,7 +10,7 @@
 
   
   
-  torch_tensorrt.ts — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  torch_tensorrt.ts — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -691,7 +691,7 @@ 
    Functions
 
    
-torch_tensorrt.ts.TensorRTCompileSpec(inputs: Optional[List[torch.Tensor | Input]] = None, input_signature: Optional[Any] = None, device: Optional[Union[device, Device]] = None, disable_tf32: bool = False, sparse_weights: bool = False, enabled_precisions: Optional[Set[Union[dtype, dtype]]] = None, refit: bool = False, debug: bool = False, capability: EngineCapability = EngineCapability.STANDARD, num_avg_timing_iters: int = 1, workspace_size: int = 0, dla_sram_size: int = 1048576, dla_local_dram_size: int = 1073741824, dla_global_dram_size: int = 536870912, truncate_long_and_double: bool = False, calibrator: object = None, allow_shape_tensors: bool = False) → <torch.ScriptClass object at 0x7f690a9985b0>[source]
    
+torch_tensorrt.ts.TensorRTCompileSpec(inputs: Optional[List[torch.Tensor | Input]] = None, input_signature: Optional[Any] = None, device: Optional[Union[device, Device]] = None, disable_tf32: bool = False, sparse_weights: bool = False, enabled_precisions: Optional[Set[Union[dtype, dtype]]] = None, refit: bool = False, debug: bool = False, capability: EngineCapability = EngineCapability.STANDARD, num_avg_timing_iters: int = 1, workspace_size: int = 0, dla_sram_size: int = 1048576, dla_local_dram_size: int = 1073741824, dla_global_dram_size: int = 536870912, truncate_long_and_double: bool = False, calibrator: object = None, allow_shape_tensors: bool = False) → <torch.ScriptClass object at 0x7f986f00f930>[source]
 
    Utility to create a formatted spec dictionary for using the PyTorch TensorRT backend
    
 
    
 
    Keyword Arguments
    
diff --git a/docs/search.html b/docs/search.html
index 567ad1a4dd..dd9e700116 100644
--- a/docs/search.html
+++ b/docs/search.html
@@ -9,7 +9,7 @@
   
   
   
-  Search — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Search — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -272,7 +272,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/searchindex.js b/docs/searchindex.js
index b15267481d..73159431fe 100644
--- a/docs/searchindex.js
+++ b/docs/searchindex.js
@@ -1 +1 @@
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@@ -273,7 +273,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/src/pytorch-sphinx-theme/docs/demo/demo.html b/docs/src/pytorch-sphinx-theme/docs/demo/demo.html
index fcdfd7efad..ad54ecb6aa 100644
--- a/docs/src/pytorch-sphinx-theme/docs/demo/demo.html
+++ b/docs/src/pytorch-sphinx-theme/docs/demo/demo.html
@@ -12,7 +12,7 @@
 
   
   
-  3. Paragraph Level Markup — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  3. Paragraph Level Markup — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -664,7 +664,7 @@ 
    3.4.4. 
 
    3.4.5. Code Blocks
    
 
    # parsed-literal test
-curl -O http://someurl/release-v2.6.0.dev0+a945aeb.tar-gz
    
+curl -O http://someurl/release-v2.6.0.dev0+93b5b8f.tar-gz
    
 
    
 
    Code Blocks can have captions.
    
 
    {
diff --git a/docs/src/pytorch-sphinx-theme/docs/demo/lists_tables.html b/docs/src/pytorch-sphinx-theme/docs/demo/lists_tables.html
index c098019c56..cda8493459 100644
--- a/docs/src/pytorch-sphinx-theme/docs/demo/lists_tables.html
+++ b/docs/src/pytorch-sphinx-theme/docs/demo/lists_tables.html
@@ -10,7 +10,7 @@
 
   
   
-  4. Lists & Tables — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  4. Lists & Tables — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -273,7 +273,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/src/pytorch-sphinx-theme/docs/demo/long.html b/docs/src/pytorch-sphinx-theme/docs/demo/long.html
index dde528db37..5a51396ada 100644
--- a/docs/src/pytorch-sphinx-theme/docs/demo/long.html
+++ b/docs/src/pytorch-sphinx-theme/docs/demo/long.html
@@ -10,7 +10,7 @@
 
   
   
-  1. Long Sticky Nav — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  1. Long Sticky Nav — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -273,7 +273,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/src/pytorch-sphinx-theme/docs/demo/structure.html b/docs/src/pytorch-sphinx-theme/docs/demo/structure.html
index eaba1477d7..515d65f72b 100644
--- a/docs/src/pytorch-sphinx-theme/docs/demo/structure.html
+++ b/docs/src/pytorch-sphinx-theme/docs/demo/structure.html
@@ -10,7 +10,7 @@
 
   
   
-  1. Structural Elements — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  1. Structural Elements — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -273,7 +273,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/src/pytorch-sphinx-theme/docs/index.html b/docs/src/pytorch-sphinx-theme/docs/index.html
index 34967e25e5..a48cb34796 100644
--- a/docs/src/pytorch-sphinx-theme/docs/index.html
+++ b/docs/src/pytorch-sphinx-theme/docs/index.html
@@ -10,7 +10,7 @@
 
   
   
-  <no title> — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  <no title> — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -273,7 +273,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/src/pytorch-sphinx-theme/docs/installing.html b/docs/src/pytorch-sphinx-theme/docs/installing.html
index 850745efbd..0f1ffaba46 100644
--- a/docs/src/pytorch-sphinx-theme/docs/installing.html
+++ b/docs/src/pytorch-sphinx-theme/docs/installing.html
@@ -10,7 +10,7 @@
 
   
   
-  Installation — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Installation — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -273,7 +273,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/ts/creating_torchscript_module_in_python.html b/docs/ts/creating_torchscript_module_in_python.html
index 77938e826c..891126fc34 100644
--- a/docs/ts/creating_torchscript_module_in_python.html
+++ b/docs/ts/creating_torchscript_module_in_python.html
@@ -10,7 +10,7 @@
 
   
   
-  Creating a TorchScript Module — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Creating a TorchScript Module — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/ts/getting_started_with_cpp_api.html b/docs/ts/getting_started_with_cpp_api.html
index 24f97339c2..055e4c0131 100644
--- a/docs/ts/getting_started_with_cpp_api.html
+++ b/docs/ts/getting_started_with_cpp_api.html
@@ -10,7 +10,7 @@
 
   
   
-  Using Torch-TensorRT in C++ — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Using Torch-TensorRT in C++ — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/ts/getting_started_with_python_api.html b/docs/ts/getting_started_with_python_api.html
index d9d7cd765c..958f609366 100644
--- a/docs/ts/getting_started_with_python_api.html
+++ b/docs/ts/getting_started_with_python_api.html
@@ -10,7 +10,7 @@
 
   
   
-  Using Torch-TensorRT in Python — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Using Torch-TensorRT in Python — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/ts/ptq.html b/docs/ts/ptq.html
index b4133e1795..9443c30a50 100644
--- a/docs/ts/ptq.html
+++ b/docs/ts/ptq.html
@@ -10,7 +10,7 @@
 
   
   
-  Post Training Quantization (PTQ) — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Post Training Quantization (PTQ) — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/ts/torchscript_frontend_from_pytorch.html b/docs/ts/torchscript_frontend_from_pytorch.html
index 8db994ee5f..9b9c3f055f 100644
--- a/docs/ts/torchscript_frontend_from_pytorch.html
+++ b/docs/ts/torchscript_frontend_from_pytorch.html
@@ -10,7 +10,7 @@
 
   
   
-  Using Torch-TensorRT TorchScript Frontend Directly From PyTorch — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Using Torch-TensorRT TorchScript Frontend Directly From PyTorch — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -273,7 +273,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/tutorials/_rendered_examples/dynamo/converter_overloading.html b/docs/tutorials/_rendered_examples/dynamo/converter_overloading.html
index 7dc7565fcf..35765c7133 100644
--- a/docs/tutorials/_rendered_examples/dynamo/converter_overloading.html
+++ b/docs/tutorials/_rendered_examples/dynamo/converter_overloading.html
@@ -10,7 +10,7 @@
 
   
   
-  Overloading Torch-TensorRT Converters with Custom Converters — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Overloading Torch-TensorRT Converters with Custom Converters — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/tutorials/_rendered_examples/dynamo/cross_runtime_compilation_for_windows.html b/docs/tutorials/_rendered_examples/dynamo/cross_runtime_compilation_for_windows.html
index 850dcc13e2..8853e3367b 100644
--- a/docs/tutorials/_rendered_examples/dynamo/cross_runtime_compilation_for_windows.html
+++ b/docs/tutorials/_rendered_examples/dynamo/cross_runtime_compilation_for_windows.html
@@ -10,7 +10,7 @@
 
   
   
-  Cross runtime compilation for windows example — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Cross runtime compilation for windows example — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -273,7 +273,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html b/docs/tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html
index 1004b98547..732399bc43 100644
--- a/docs/tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html
+++ b/docs/tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html
@@ -10,7 +10,7 @@
 
   
   
-  Using Custom Kernels within TensorRT Engines with Torch-TensorRT — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Using Custom Kernels within TensorRT Engines with Torch-TensorRT — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/tutorials/_rendered_examples/dynamo/engine_caching_bert_example.html b/docs/tutorials/_rendered_examples/dynamo/engine_caching_bert_example.html
index 0e28fc7f13..5617d08539 100644
--- a/docs/tutorials/_rendered_examples/dynamo/engine_caching_bert_example.html
+++ b/docs/tutorials/_rendered_examples/dynamo/engine_caching_bert_example.html
@@ -10,7 +10,7 @@
 
   
   
-  Engine Caching (BERT) — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Engine Caching (BERT) — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -519,7 +519,7 @@
             "truncate_double": True,
             "debug": False,
             "min_block_size": 1,
-            "make_refittable": True,
+            "immutable_weights": False,
             "cache_built_engines": cache_built_engines,
             "reuse_cached_engines": reuse_cached_engines,
             "engine_cache_dir": "/tmp/torch_trt_bert_engine_cache",
diff --git a/docs/tutorials/_rendered_examples/dynamo/engine_caching_example.html b/docs/tutorials/_rendered_examples/dynamo/engine_caching_example.html
index e507e9c70b..a6153e56cc 100644
--- a/docs/tutorials/_rendered_examples/dynamo/engine_caching_example.html
+++ b/docs/tutorials/_rendered_examples/dynamo/engine_caching_example.html
@@ -10,7 +10,7 @@
 
   
   
-  Engine Caching — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Engine Caching — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -529,7 +529,7 @@ 
    Engine Caching for JIT Compilationcache_built_engines=True),
-the engine must be refittable (make_refittable=True). See Refitting Torch-TensorRT Programs with New Weights for more details.
    
+the engine must be refittable (immutable_weights=False). See Refitting Torch-TensorRT Programs with New Weights for more details.
    
 
    def torch_compile(iterations=3):
     times = []
     start = torch.cuda.Event(enable_timing=True)
@@ -561,7 +561,7 @@ 
    Engine Caching for JIT Compilation"enabled_precisions": enabled_precisions,
                 "debug": debug,
                 "min_block_size": min_block_size,
-                "make_refittable": True,
+                "immutable_weights": False,
                 "cache_built_engines": cache_built_engines,
                 "reuse_cached_engines": reuse_cached_engines,
             },
@@ -620,7 +620,7 @@ 
    Engine Caching for AOT Compilationenabled_precisions=enabled_precisions,
             debug=debug,
             min_block_size=min_block_size,
-            make_refittable=True,
+            immutable_weights=False,
             cache_built_engines=cache_built_engines,
             reuse_cached_engines=reuse_cached_engines,
             engine_cache_size=1 << 30,  # 1GB
@@ -730,7 +730,7 @@ 
    Custom Engine Cache"enabled_precisions": enabled_precisions,
                 "debug": debug,
                 "min_block_size": min_block_size,
-                "make_refittable": True,
+                "immutable_weights": False,
                 "cache_built_engines": cache_built_engines,
                 "reuse_cached_engines": reuse_cached_engines,
                 "custom_engine_cache": engine_cache,
diff --git a/docs/tutorials/_rendered_examples/dynamo/index.html b/docs/tutorials/_rendered_examples/dynamo/index.html
index 65fc6c9c1b..106992e415 100644
--- a/docs/tutorials/_rendered_examples/dynamo/index.html
+++ b/docs/tutorials/_rendered_examples/dynamo/index.html
@@ -10,7 +10,7 @@
 
   
   
-  Dependencies — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Dependencies — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -273,7 +273,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html b/docs/tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html
index b0ff6a0969..5d2928a6c6 100644
--- a/docs/tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html
+++ b/docs/tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html
@@ -10,7 +10,7 @@
 
   
   
-  Mutable Torch TensorRT Module — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Mutable Torch TensorRT Module — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -497,7 +497,7 @@ 
    Initialize the Mutable Torch TensorRT Module with settings.
    settings = {
     "use_python": False,
     "enabled_precisions": {torch.float32},
-    "make_refittable": True,
+    "immutable_weights": False,
 }
 
 model = models.resnet18(pretrained=True).eval().to("cuda")
@@ -545,7 +545,7 @@ 
    Stable Diffusion with Huggingface"use_python_runtime": True,
         "enabled_precisions": {torch.float16},
         "debug": True,
-        "make_refittable": True,
+        "immutable_weights": False,
     }
 
     model_id = "runwayml/stable-diffusion-v1-5"
diff --git a/docs/tutorials/_rendered_examples/dynamo/refit_engine_example.html b/docs/tutorials/_rendered_examples/dynamo/refit_engine_example.html
index f8eeb0a6cf..4cce8e83d1 100644
--- a/docs/tutorials/_rendered_examples/dynamo/refit_engine_example.html
+++ b/docs/tutorials/_rendered_examples/dynamo/refit_engine_example.html
@@ -10,7 +10,7 @@
 
   
   
-  Refitting Torch-TensorRT Programs with New Weights — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Refitting Torch-TensorRT Programs with New Weights — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
@@ -512,7 +512,7 @@ 
    Imports and model definition
 
    Make a refittable Compilation Program
    
 
    The inital step is to compile a module and save it as with a normal. Note that there is an
-additional parameter make_refittable that is set to True. This parameter is used to
+additional parameter immutable_weights that is set to False. This parameter is used to
 indicate that the engine being built should support weight refitting later. Engines built without
 these setttings will not be able to be refit.
    
 
    In this case we are going to compile a ResNet18 model with randomly initialized weights and save it.
    
@@ -532,7 +532,7 @@ 
    Make a refittable Compilation Programdebug=debug,
     min_block_size=min_block_size,
     torch_executed_ops=torch_executed_ops,
-    make_refittable=True,
+    immutable_weights=False,
     reuse_cached_engines=False,
 )  # Output is a torch.fx.GraphModule
 
diff --git a/docs/tutorials/_rendered_examples/dynamo/torch_compile_advanced_usage.html b/docs/tutorials/_rendered_examples/dynamo/torch_compile_advanced_usage.html
index fa31cc2854..ed8ddce587 100644
--- a/docs/tutorials/_rendered_examples/dynamo/torch_compile_advanced_usage.html
+++ b/docs/tutorials/_rendered_examples/dynamo/torch_compile_advanced_usage.html
@@ -10,7 +10,7 @@
 
   
   
-  Torch Compile Advanced Usage — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Torch Compile Advanced Usage — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html b/docs/tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html
index cb19831f70..01a1d248cc 100644
--- a/docs/tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html
+++ b/docs/tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html
@@ -10,7 +10,7 @@
 
   
   
-  Compiling ResNet with dynamic shapes using the torch.compile backend — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Compiling ResNet with dynamic shapes using the torch.compile backend — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html b/docs/tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html
index c0fc6409cf..194cf20342 100644
--- a/docs/tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html
+++ b/docs/tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html
@@ -10,7 +10,7 @@
 
   
   
-  Compiling Stable Diffusion model using the torch.compile backend — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Compiling Stable Diffusion model using the torch.compile backend — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html b/docs/tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html
index 09d29e00de..0634ae8f7a 100644
--- a/docs/tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html
+++ b/docs/tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html
@@ -10,7 +10,7 @@
 
   
   
-  Compiling BERT using the torch.compile backend — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Compiling BERT using the torch.compile backend — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html b/docs/tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html
index 9948251940..a3e2b692f4 100644
--- a/docs/tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html
+++ b/docs/tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html
@@ -10,7 +10,7 @@
 
   
   
-  Torch Export with Cudagraphs — Torch-TensorRT v2.6.0.dev0+a945aeb documentation
+  Torch Export with Cudagraphs — Torch-TensorRT v2.6.0.dev0+93b5b8f documentation
   
 
   
@@ -275,7 +275,7 @@
               
               
                 
    
-                  v2.6.0.dev0+a945aeb
+                  v2.6.0.dev0+93b5b8f
                 
    
               
             
diff --git a/docs/tutorials/_rendered_examples/dynamo/torch_export_gpt2.html b/docs/tutorials/_rendered_examples/dynamo/torch_export_gpt2.html
index 9322e5949a..1ed55ba683 100644
--- a/docs/tutorials/_rendered_examples/dynamo/torch_export_gpt2.html
+++ b/docs/tutorials/_rendered_examples/dynamo/torch_export_gpt2.html
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@@ -10,7 +10,7 @@
 
   
   
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@@ -275,7 +275,7 @@
               
               
                 
    
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@@ -10,7 +10,7 @@
 
   
   
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